Overview

Dataset statistics

Number of variables35
Number of observations35
Missing cells223
Missing cells (%)18.2%
Duplicate rows2
Duplicate rows (%)5.7%
Total size in memory9.7 KiB
Average record size in memory284.8 B

Variable types

Unsupported1
Text33
DateTime1

Dataset

Description2022-09-16
Author주민등록인구통계
URLhttps://bigdata.gwangju.go.kr/usr/dataSet/getDataDetailView.rd?dataSetUncd=DS000201927

Alerts

Unnamed: 12 has constant value ""Constant
Dataset has 2 (5.7%) duplicate rowsDuplicates
Unnamed: 0 has 35 (100.0%) missing valuesMissing
인구이동보고서(1호) has 19 (54.3%) missing valuesMissing
Unnamed: 2 has 24 (68.6%) missing valuesMissing
Unnamed: 3 has 23 (65.7%) missing valuesMissing
Unnamed: 4 has 31 (88.6%) missing valuesMissing
Unnamed: 5 has 2 (5.7%) missing valuesMissing
Unnamed: 6 has 2 (5.7%) missing valuesMissing
Unnamed: 7 has 2 (5.7%) missing valuesMissing
Unnamed: 8 has 2 (5.7%) missing valuesMissing
Unnamed: 9 has 2 (5.7%) missing valuesMissing
Unnamed: 10 has 1 (2.9%) missing valuesMissing
Unnamed: 11 has 2 (5.7%) missing valuesMissing
Unnamed: 12 has 34 (97.1%) missing valuesMissing
Unnamed: 13 has 2 (5.7%) missing valuesMissing
Unnamed: 14 has 2 (5.7%) missing valuesMissing
Unnamed: 15 has 2 (5.7%) missing valuesMissing
Unnamed: 16 has 2 (5.7%) missing valuesMissing
Unnamed: 17 has 2 (5.7%) missing valuesMissing
Unnamed: 18 has 2 (5.7%) missing valuesMissing
Unnamed: 19 has 2 (5.7%) missing valuesMissing
Unnamed: 20 has 2 (5.7%) missing valuesMissing
Unnamed: 21 has 2 (5.7%) missing valuesMissing
Unnamed: 22 has 2 (5.7%) missing valuesMissing
Unnamed: 23 has 2 (5.7%) missing valuesMissing
Unnamed: 24 has 2 (5.7%) missing valuesMissing
Unnamed: 25 has 2 (5.7%) missing valuesMissing
Unnamed: 26 has 2 (5.7%) missing valuesMissing
Unnamed: 27 has 2 (5.7%) missing valuesMissing
Unnamed: 28 has 2 (5.7%) missing valuesMissing
Unnamed: 29 has 2 (5.7%) missing valuesMissing
Unnamed: 30 has 2 (5.7%) missing valuesMissing
Unnamed: 31 has 2 (5.7%) missing valuesMissing
Unnamed: 32 has 2 (5.7%) missing valuesMissing
Unnamed: 33 has 2 (5.7%) missing valuesMissing
Unnamed: 34 has 2 (5.7%) missing valuesMissing
Unnamed: 0 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-02-10 09:44:57.761647
Analysis finished2024-02-10 09:44:59.404473
Duration1.64 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

Unnamed: 0
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing35
Missing (%)100.0%
Memory size447.0 B
Distinct16
Distinct (%)100.0%
Missing19
Missing (%)54.3%
Memory size412.0 B
2024-02-10T09:44:59.632030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10.5
Mean length7.875
Min length5

Characters and Unicode

Total characters126
Distinct characters43
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique16 ?
Unique (%)100.0%

Sample

1st row행정기관 :
2nd row작성기준 :
3rd row시, 군, 구(읍면동)
4th row전월말세대수
5th row전월말인구수
ValueCountFrequency (%)
2
 
7.7%
2
 
7.7%
2
 
7.7%
금월말거주불명자수 1
 
3.8%
금월말인구수 1
 
3.8%
금월말세대수 1
 
3.8%
거주불명자수증감 1
 
3.8%
인구수증감 1
 
3.8%
세대수증감 1
 
3.8%
1
 
3.8%
Other values (13) 13
50.0%
2024-02-10T09:45:00.590640image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
12
 
9.5%
11
 
8.7%
8
 
6.3%
8
 
6.3%
5
 
4.0%
5
 
4.0%
4
 
3.2%
4
 
3.2%
4
 
3.2%
4
 
3.2%
Other values (33) 61
48.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 104
82.5%
Control 12
 
9.5%
Space Separator 4
 
3.2%
Other Punctuation 4
 
3.2%
Open Punctuation 1
 
0.8%
Close Punctuation 1
 
0.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
11
 
10.6%
8
 
7.7%
8
 
7.7%
5
 
4.8%
5
 
4.8%
4
 
3.8%
4
 
3.8%
4
 
3.8%
4
 
3.8%
4
 
3.8%
Other values (27) 47
45.2%
Other Punctuation
ValueCountFrequency (%)
, 2
50.0%
: 2
50.0%
Control
ValueCountFrequency (%)
12
100.0%
Space Separator
ValueCountFrequency (%)
4
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 104
82.5%
Common 22
 
17.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
11
 
10.6%
8
 
7.7%
8
 
7.7%
5
 
4.8%
5
 
4.8%
4
 
3.8%
4
 
3.8%
4
 
3.8%
4
 
3.8%
4
 
3.8%
Other values (27) 47
45.2%
Common
ValueCountFrequency (%)
12
54.5%
4
 
18.2%
, 2
 
9.1%
: 2
 
9.1%
( 1
 
4.5%
) 1
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 104
82.5%
ASCII 22
 
17.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
12
54.5%
4
 
18.2%
, 2
 
9.1%
: 2
 
9.1%
( 1
 
4.5%
) 1
 
4.5%
Hangul
ValueCountFrequency (%)
11
 
10.6%
8
 
7.7%
8
 
7.7%
5
 
4.8%
5
 
4.8%
4
 
3.8%
4
 
3.8%
4
 
3.8%
4
 
3.8%
4
 
3.8%
Other values (27) 47
45.2%

Unnamed: 2
Text

MISSING 

Distinct9
Distinct (%)81.8%
Missing24
Missing (%)68.6%
Memory size412.0 B
2024-02-10T09:45:01.069620image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length2
Mean length2.3636364
Min length2

Characters and Unicode

Total characters26
Distinct characters17
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7 ?
Unique (%)63.6%

Sample

1st row전 입
2nd row복귀
3rd row출생
4th row등록
5th row국외
ValueCountFrequency (%)
국외 2
15.4%
기타 2
15.4%
2
15.4%
1
7.7%
복귀 1
7.7%
출생 1
7.7%
등록 1
7.7%
1
7.7%
사망 1
7.7%
말소 1
7.7%
2024-02-10T09:45:01.905122image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4
15.4%
2
 
7.7%
2
 
7.7%
2
 
7.7%
2
 
7.7%
2
 
7.7%
2
 
7.7%
1
 
3.8%
1
 
3.8%
1
 
3.8%
Other values (7) 7
26.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 22
84.6%
Control 4
 
15.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
2
 
9.1%
2
 
9.1%
2
 
9.1%
2
 
9.1%
2
 
9.1%
2
 
9.1%
1
 
4.5%
1
 
4.5%
1
 
4.5%
1
 
4.5%
Other values (6) 6
27.3%
Control
ValueCountFrequency (%)
4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 22
84.6%
Common 4
 
15.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
2
 
9.1%
2
 
9.1%
2
 
9.1%
2
 
9.1%
2
 
9.1%
2
 
9.1%
1
 
4.5%
1
 
4.5%
1
 
4.5%
1
 
4.5%
Other values (6) 6
27.3%
Common
ValueCountFrequency (%)
4
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 22
84.6%
ASCII 4
 
15.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4
100.0%
Hangul
ValueCountFrequency (%)
2
 
9.1%
2
 
9.1%
2
 
9.1%
2
 
9.1%
2
 
9.1%
2
 
9.1%
1
 
4.5%
1
 
4.5%
1
 
4.5%
1
 
4.5%
Other values (6) 6
27.3%

Unnamed: 3
Text

MISSING 

Distinct7
Distinct (%)58.3%
Missing23
Missing (%)65.7%
Memory size412.0 B
2024-02-10T09:45:02.268505image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length9
Mean length3.4166667
Min length1

Characters and Unicode

Total characters41
Distinct characters20
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)16.7%

Sample

1st row광주광역시 북구
2nd row2022.08 현재
3rd row
4th row남자
5th row여자
ValueCountFrequency (%)
2
14.3%
남자 2
14.3%
여자 2
14.3%
시도내 2
14.3%
시도간 2
14.3%
광주광역시 1
7.1%
북구 1
7.1%
2022.08 1
7.1%
현재 1
7.1%
2024-02-10T09:45:03.011651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5
12.2%
4
 
9.8%
4
 
9.8%
3
 
7.3%
2 3
 
7.3%
2
 
4.9%
0 2
 
4.9%
2
 
4.9%
2
 
4.9%
2
 
4.9%
Other values (10) 12
29.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 31
75.6%
Decimal Number 6
 
14.6%
Space Separator 3
 
7.3%
Other Punctuation 1
 
2.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
5
16.1%
4
12.9%
4
12.9%
2
 
6.5%
2
 
6.5%
2
 
6.5%
2
 
6.5%
2
 
6.5%
2
 
6.5%
1
 
3.2%
Other values (5) 5
16.1%
Decimal Number
ValueCountFrequency (%)
2 3
50.0%
0 2
33.3%
8 1
 
16.7%
Space Separator
ValueCountFrequency (%)
3
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 31
75.6%
Common 10
 
24.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
5
16.1%
4
12.9%
4
12.9%
2
 
6.5%
2
 
6.5%
2
 
6.5%
2
 
6.5%
2
 
6.5%
2
 
6.5%
1
 
3.2%
Other values (5) 5
16.1%
Common
ValueCountFrequency (%)
3
30.0%
2 3
30.0%
0 2
20.0%
8 1
 
10.0%
. 1
 
10.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 31
75.6%
ASCII 10
 
24.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
5
16.1%
4
12.9%
4
12.9%
2
 
6.5%
2
 
6.5%
2
 
6.5%
2
 
6.5%
2
 
6.5%
2
 
6.5%
1
 
3.2%
Other values (5) 5
16.1%
ASCII
ValueCountFrequency (%)
3
30.0%
2 3
30.0%
0 2
20.0%
8 1
 
10.0%
. 1
 
10.0%

Unnamed: 4
Text

MISSING 

Distinct2
Distinct (%)50.0%
Missing31
Missing (%)88.6%
Memory size412.0 B
2024-02-10T09:45:03.330842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length4
Mean length4
Min length4

Characters and Unicode

Total characters16
Distinct characters5
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row시군구내
2nd row시군구간
3rd row시군구내
4th row시군구간
ValueCountFrequency (%)
시군구내 2
50.0%
시군구간 2
50.0%
2024-02-10T09:45:03.867514image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4
25.0%
4
25.0%
4
25.0%
2
12.5%
2
12.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 16
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
4
25.0%
4
25.0%
4
25.0%
2
12.5%
2
12.5%

Most occurring scripts

ValueCountFrequency (%)
Hangul 16
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
4
25.0%
4
25.0%
4
25.0%
2
12.5%
2
12.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 16
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
4
25.0%
4
25.0%
4
25.0%
2
12.5%
2
12.5%

Unnamed: 5
Text

MISSING 

Distinct28
Distinct (%)84.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:45:04.183611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length4.030303
Min length1

Characters and Unicode

Total characters133
Distinct characters15
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique26 ?
Unique (%)78.8%

Sample

1st row합 계
2nd row197,542
3rd row425,881
4th row1,270
5th row221
ValueCountFrequency (%)
0 5
 
14.7%
1,595 2
 
5.9%
2,645 1
 
2.9%
2,704 1
 
2.9%
1,268 1
 
2.9%
424,715 1
 
2.9%
197,556 1
 
2.9%
2 1
 
2.9%
1,166 1
 
2.9%
14 1
 
2.9%
Other values (19) 19
55.9%
2024-02-10T09:45:05.079135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 20
15.0%
, 19
14.3%
2 19
14.3%
5 16
12.0%
0 12
9.0%
4 12
9.0%
6 8
 
6.0%
9 7
 
5.3%
7 6
 
4.5%
8 6
 
4.5%
Other values (5) 8
 
6.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 108
81.2%
Other Punctuation 19
 
14.3%
Space Separator 2
 
1.5%
Dash Punctuation 2
 
1.5%
Other Letter 2
 
1.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 20
18.5%
2 19
17.6%
5 16
14.8%
0 12
11.1%
4 12
11.1%
6 8
 
7.4%
9 7
 
6.5%
7 6
 
5.6%
8 6
 
5.6%
3 2
 
1.9%
Other Letter
ValueCountFrequency (%)
1
50.0%
1
50.0%
Other Punctuation
ValueCountFrequency (%)
, 19
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 131
98.5%
Hangul 2
 
1.5%

Most frequent character per script

Common
ValueCountFrequency (%)
1 20
15.3%
, 19
14.5%
2 19
14.5%
5 16
12.2%
0 12
9.2%
4 12
9.2%
6 8
 
6.1%
9 7
 
5.3%
7 6
 
4.6%
8 6
 
4.6%
Other values (3) 6
 
4.6%
Hangul
ValueCountFrequency (%)
1
50.0%
1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 131
98.5%
Hangul 2
 
1.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 20
15.3%
, 19
14.5%
2 19
14.5%
5 16
12.2%
0 12
9.2%
4 12
9.2%
6 8
 
6.1%
9 7
 
5.3%
7 6
 
4.6%
8 6
 
4.6%
Other values (3) 6
 
4.6%
Hangul
ValueCountFrequency (%)
1
50.0%
1
50.0%

Unnamed: 6
Text

MISSING 

Distinct23
Distinct (%)69.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:45:05.326746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length2.1515152
Min length1

Characters and Unicode

Total characters71
Distinct characters15
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique20 ?
Unique (%)60.6%

Sample

1st row중흥1동
2nd row2,997
3rd row4,723
4th row54
5th row0
ValueCountFrequency (%)
0 9
27.3%
45 2
 
6.1%
1 2
 
6.1%
11 2
 
6.1%
33 1
 
3.0%
78 1
 
3.0%
4,674 1
 
3.0%
2,974 1
 
3.0%
49 1
 
3.0%
23 1
 
3.0%
Other values (12) 12
36.4%
2024-02-10T09:45:06.073659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 11
15.5%
1 10
14.1%
4 10
14.1%
2 7
9.9%
3 7
9.9%
7 5
7.0%
5 4
 
5.6%
, 4
 
5.6%
9 4
 
5.6%
- 3
 
4.2%
Other values (5) 6
8.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 61
85.9%
Other Punctuation 4
 
5.6%
Dash Punctuation 3
 
4.2%
Other Letter 3
 
4.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 11
18.0%
1 10
16.4%
4 10
16.4%
2 7
11.5%
3 7
11.5%
7 5
8.2%
5 4
 
6.6%
9 4
 
6.6%
6 2
 
3.3%
8 1
 
1.6%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 68
95.8%
Hangul 3
 
4.2%

Most frequent character per script

Common
ValueCountFrequency (%)
0 11
16.2%
1 10
14.7%
4 10
14.7%
2 7
10.3%
3 7
10.3%
7 5
7.4%
5 4
 
5.9%
, 4
 
5.9%
9 4
 
5.9%
- 3
 
4.4%
Other values (2) 3
 
4.4%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 68
95.8%
Hangul 3
 
4.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 11
16.2%
1 10
14.7%
4 10
14.7%
2 7
10.3%
3 7
10.3%
7 5
7.4%
5 4
 
5.9%
, 4
 
5.9%
9 4
 
5.9%
- 3
 
4.4%
Other values (2) 3
 
4.4%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 7
Text

MISSING 

Distinct26
Distinct (%)78.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:45:06.333379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length2.1212121
Min length1

Characters and Unicode

Total characters70
Distinct characters14
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique24 ?
Unique (%)72.7%

Sample

1st row중흥2동
2nd row4,449
3rd row8,532
4th row61
5th row6
ValueCountFrequency (%)
0 7
21.2%
6 2
 
6.1%
77 1
 
3.0%
8,548 1
 
3.0%
4,463 1
 
3.0%
1 1
 
3.0%
16 1
 
3.0%
14 1
 
3.0%
7 1
 
3.0%
48 1
 
3.0%
Other values (16) 16
48.5%
2024-02-10T09:45:07.144264image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4 11
15.7%
6 8
11.4%
0 7
10.0%
1 7
10.0%
2 7
10.0%
8 5
7.1%
5 5
7.1%
3 5
7.1%
7 5
7.1%
, 4
 
5.7%
Other values (4) 6
8.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 63
90.0%
Other Punctuation 4
 
5.7%
Other Letter 3
 
4.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 11
17.5%
6 8
12.7%
0 7
11.1%
1 7
11.1%
2 7
11.1%
8 5
7.9%
5 5
7.9%
3 5
7.9%
7 5
7.9%
9 3
 
4.8%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 67
95.7%
Hangul 3
 
4.3%

Most frequent character per script

Common
ValueCountFrequency (%)
4 11
16.4%
6 8
11.9%
0 7
10.4%
1 7
10.4%
2 7
10.4%
8 5
7.5%
5 5
7.5%
3 5
7.5%
7 5
7.5%
, 4
 
6.0%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 67
95.7%
Hangul 3
 
4.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4 11
16.4%
6 8
11.9%
0 7
10.4%
1 7
10.4%
2 7
10.4%
8 5
7.5%
5 5
7.5%
3 5
7.5%
7 5
7.5%
, 4
 
6.0%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 8
Text

MISSING 

Distinct25
Distinct (%)75.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:45:07.486975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length2.1212121
Min length1

Characters and Unicode

Total characters70
Distinct characters14
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique22 ?
Unique (%)66.7%

Sample

1st row중흥3동
2nd row3,598
3rd row6,530
4th row42
5th row3
ValueCountFrequency (%)
0 7
21.2%
38 2
 
6.1%
3 2
 
6.1%
9 1
 
3.0%
46 1
 
3.0%
6,579 1
 
3.0%
3,626 1
 
3.0%
10 1
 
3.0%
49 1
 
3.0%
28 1
 
3.0%
Other values (15) 15
45.5%
2024-02-10T09:45:08.451644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 10
14.3%
0 9
12.9%
6 9
12.9%
5 8
11.4%
9 6
8.6%
2 6
8.6%
4 5
7.1%
8 4
 
5.7%
, 4
 
5.7%
1 3
 
4.3%
Other values (4) 6
8.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 63
90.0%
Other Punctuation 4
 
5.7%
Other Letter 3
 
4.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 10
15.9%
0 9
14.3%
6 9
14.3%
5 8
12.7%
9 6
9.5%
2 6
9.5%
4 5
7.9%
8 4
 
6.3%
1 3
 
4.8%
7 3
 
4.8%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 67
95.7%
Hangul 3
 
4.3%

Most frequent character per script

Common
ValueCountFrequency (%)
3 10
14.9%
0 9
13.4%
6 9
13.4%
5 8
11.9%
9 6
9.0%
2 6
9.0%
4 5
7.5%
8 4
 
6.0%
, 4
 
6.0%
1 3
 
4.5%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 67
95.7%
Hangul 3
 
4.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 10
14.9%
0 9
13.4%
6 9
13.4%
5 8
11.9%
9 6
9.0%
2 6
9.0%
4 5
7.5%
8 4
 
6.0%
, 4
 
6.0%
1 3
 
4.5%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 9
Text

MISSING 

Distinct23
Distinct (%)69.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:45:08.801712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
Mean length2.0606061
Min length1

Characters and Unicode

Total characters68
Distinct characters15
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique20 ?
Unique (%)60.6%

Sample

1st row중앙동
2nd row2,407
3rd row4,054
4th row49
5th row4
ValueCountFrequency (%)
0 7
21.2%
4 4
 
12.1%
38 2
 
6.1%
85 1
 
3.0%
46 1
 
3.0%
4,045 1
 
3.0%
2,389 1
 
3.0%
1 1
 
3.0%
9 1
 
3.0%
18 1
 
3.0%
Other values (13) 13
39.4%
2024-02-10T09:45:09.628375image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 11
16.2%
4 11
16.2%
3 6
8.8%
2 6
8.8%
8 5
7.4%
9 5
7.4%
5 5
7.4%
, 4
 
5.9%
7 4
 
5.9%
1 4
 
5.9%
Other values (5) 7
10.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 59
86.8%
Other Punctuation 4
 
5.9%
Other Letter 3
 
4.4%
Dash Punctuation 2
 
2.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 11
18.6%
4 11
18.6%
3 6
10.2%
2 6
10.2%
8 5
8.5%
9 5
8.5%
5 5
8.5%
7 4
 
6.8%
1 4
 
6.8%
6 2
 
3.4%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 65
95.6%
Hangul 3
 
4.4%

Most frequent character per script

Common
ValueCountFrequency (%)
0 11
16.9%
4 11
16.9%
3 6
9.2%
2 6
9.2%
8 5
7.7%
9 5
7.7%
5 5
7.7%
, 4
 
6.2%
7 4
 
6.2%
1 4
 
6.2%
Other values (2) 4
 
6.2%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 65
95.6%
Hangul 3
 
4.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 11
16.9%
4 11
16.9%
3 6
9.2%
2 6
9.2%
8 5
7.7%
9 5
7.7%
5 5
7.7%
, 4
 
6.2%
7 4
 
6.2%
1 4
 
6.2%
Other values (2) 4
 
6.2%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 10
Text

MISSING 

Distinct26
Distinct (%)76.5%
Missing1
Missing (%)2.9%
Memory size412.0 B
2024-02-10T09:45:10.057050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.2058824
Min length1

Characters and Unicode

Total characters75
Distinct characters20
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique23 ?
Unique (%)67.6%

Sample

1st row출력일자 :
2nd row임동
3rd row4,576
4th row9,159
5th row37
ValueCountFrequency (%)
0 6
 
17.1%
5 3
 
8.6%
36 2
 
5.7%
2 2
 
5.7%
출력일자 1
 
2.9%
4,574 1
 
2.9%
1 1
 
2.9%
34 1
 
2.9%
27 1
 
2.9%
44 1
 
2.9%
Other values (16) 16
45.7%
2024-02-10T09:45:10.899914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 9
12.0%
0 8
10.7%
4 8
10.7%
3 8
10.7%
1 7
9.3%
2 6
8.0%
6 5
6.7%
, 4
 
5.3%
7 4
 
5.3%
9 4
 
5.3%
Other values (10) 12
16.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 60
80.0%
Other Letter 6
 
8.0%
Other Punctuation 5
 
6.7%
Dash Punctuation 3
 
4.0%
Space Separator 1
 
1.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 9
15.0%
0 8
13.3%
4 8
13.3%
3 8
13.3%
1 7
11.7%
2 6
10.0%
6 5
8.3%
7 4
6.7%
9 4
6.7%
8 1
 
1.7%
Other Letter
ValueCountFrequency (%)
1
16.7%
1
16.7%
1
16.7%
1
16.7%
1
16.7%
1
16.7%
Other Punctuation
ValueCountFrequency (%)
, 4
80.0%
: 1
 
20.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 69
92.0%
Hangul 6
 
8.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 9
13.0%
0 8
11.6%
4 8
11.6%
3 8
11.6%
1 7
10.1%
2 6
8.7%
6 5
7.2%
, 4
5.8%
7 4
5.8%
9 4
5.8%
Other values (4) 6
8.7%
Hangul
ValueCountFrequency (%)
1
16.7%
1
16.7%
1
16.7%
1
16.7%
1
16.7%
1
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 69
92.0%
Hangul 6
 
8.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 9
13.0%
0 8
11.6%
4 8
11.6%
3 8
11.6%
1 7
10.1%
2 6
8.7%
6 5
7.2%
, 4
5.8%
7 4
5.8%
9 4
5.8%
Other values (4) 6
8.7%
Hangul
ValueCountFrequency (%)
1
16.7%
1
16.7%
1
16.7%
1
16.7%
1
16.7%
1
16.7%

Unnamed: 11
Text

MISSING 

Distinct25
Distinct (%)75.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:45:11.262783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.1515152
Min length1

Characters and Unicode

Total characters71
Distinct characters15
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique22 ?
Unique (%)66.7%

Sample

1st row신안동
2nd row7,233
3rd row12,353
4th row88
5th row2
ValueCountFrequency (%)
0 6
18.2%
1 3
 
9.1%
12,353 2
 
6.1%
2 2
 
6.1%
5 1
 
3.0%
7,248 1
 
3.0%
15 1
 
3.0%
8 1
 
3.0%
46 1
 
3.0%
62 1
 
3.0%
Other values (14) 14
42.4%
2024-02-10T09:45:12.049153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 9
12.7%
2 8
11.3%
6 8
11.3%
3 7
9.9%
7 7
9.9%
0 6
8.5%
5 6
8.5%
8 5
7.0%
, 4
5.6%
9 4
5.6%
Other values (5) 7
9.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 63
88.7%
Other Punctuation 4
 
5.6%
Other Letter 3
 
4.2%
Dash Punctuation 1
 
1.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 9
14.3%
2 8
12.7%
6 8
12.7%
3 7
11.1%
7 7
11.1%
0 6
9.5%
5 6
9.5%
8 5
7.9%
9 4
6.3%
4 3
 
4.8%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 68
95.8%
Hangul 3
 
4.2%

Most frequent character per script

Common
ValueCountFrequency (%)
1 9
13.2%
2 8
11.8%
6 8
11.8%
3 7
10.3%
7 7
10.3%
0 6
8.8%
5 6
8.8%
8 5
7.4%
, 4
5.9%
9 4
5.9%
Other values (2) 4
5.9%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 68
95.8%
Hangul 3
 
4.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 9
13.2%
2 8
11.8%
6 8
11.8%
3 7
10.3%
7 7
10.3%
0 6
8.8%
5 6
8.8%
8 5
7.4%
, 4
5.9%
9 4
5.9%
Other values (2) 4
5.9%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 12
Date

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing34
Missing (%)97.1%
Memory size412.0 B
Minimum2022-09-13 00:00:00
Maximum2022-09-13 00:00:00
2024-02-10T09:45:12.489831image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-10T09:45:12.829557image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Unnamed: 13
Text

MISSING 

Distinct28
Distinct (%)84.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:45:13.130976image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length3
Mean length2.7272727
Min length1

Characters and Unicode

Total characters90
Distinct characters15
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique26 ?
Unique (%)78.8%

Sample

1st row용봉동
2nd row17,847
3rd row38,047
4th row124
5th row20
ValueCountFrequency (%)
0 5
 
15.2%
20 2
 
6.1%
257 1
 
3.0%
37,986 1
 
3.0%
17,882 1
 
3.0%
1 1
 
3.0%
61 1
 
3.0%
35 1
 
3.0%
3 1
 
3.0%
17 1
 
3.0%
Other values (18) 18
54.5%
2024-02-10T09:45:13.939211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 15
16.7%
1 12
13.3%
0 10
11.1%
7 9
10.0%
4 9
10.0%
3 6
 
6.7%
5 5
 
5.6%
6 5
 
5.6%
8 5
 
5.6%
9 5
 
5.6%
Other values (5) 9
10.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 81
90.0%
Other Punctuation 4
 
4.4%
Other Letter 3
 
3.3%
Dash Punctuation 2
 
2.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 15
18.5%
1 12
14.8%
0 10
12.3%
7 9
11.1%
4 9
11.1%
3 6
 
7.4%
5 5
 
6.2%
6 5
 
6.2%
8 5
 
6.2%
9 5
 
6.2%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 87
96.7%
Hangul 3
 
3.3%

Most frequent character per script

Common
ValueCountFrequency (%)
2 15
17.2%
1 12
13.8%
0 10
11.5%
7 9
10.3%
4 9
10.3%
3 6
 
6.9%
5 5
 
5.7%
6 5
 
5.7%
8 5
 
5.7%
9 5
 
5.7%
Other values (2) 6
 
6.9%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 87
96.7%
Hangul 3
 
3.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 15
17.2%
1 12
13.8%
0 10
11.5%
7 9
10.3%
4 9
10.3%
3 6
 
6.9%
5 5
 
5.7%
6 5
 
5.7%
8 5
 
5.7%
9 5
 
5.7%
Other values (2) 6
 
6.9%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 14
Text

MISSING 

Distinct25
Distinct (%)75.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:45:14.233703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.2424242
Min length1

Characters and Unicode

Total characters74
Distinct characters15
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique22 ?
Unique (%)66.7%

Sample

1st row운암1동
2nd row7,463
3rd row19,140
4th row27
5th row18
ValueCountFrequency (%)
0 7
21.2%
18 2
 
6.1%
27 2
 
6.1%
7 1
 
3.0%
187 1
 
3.0%
7,466 1
 
3.0%
41 1
 
3.0%
3 1
 
3.0%
5 1
 
3.0%
65 1
 
3.0%
Other values (15) 15
45.5%
2024-02-10T09:45:14.919017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 11
14.9%
1 11
14.9%
6 8
10.8%
7 7
9.5%
9 7
9.5%
3 6
8.1%
4 5
6.8%
5 5
6.8%
8 4
 
5.4%
, 4
 
5.4%
Other values (5) 6
8.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 66
89.2%
Other Punctuation 4
 
5.4%
Other Letter 3
 
4.1%
Dash Punctuation 1
 
1.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 11
16.7%
1 11
16.7%
6 8
12.1%
7 7
10.6%
9 7
10.6%
3 6
9.1%
4 5
7.6%
5 5
7.6%
8 4
 
6.1%
2 2
 
3.0%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 71
95.9%
Hangul 3
 
4.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 11
15.5%
1 11
15.5%
6 8
11.3%
7 7
9.9%
9 7
9.9%
3 6
8.5%
4 5
7.0%
5 5
7.0%
8 4
 
5.6%
, 4
 
5.6%
Other values (2) 3
 
4.2%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 71
95.9%
Hangul 3
 
4.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 11
15.5%
1 11
15.5%
6 8
11.3%
7 7
9.9%
9 7
9.9%
3 6
8.5%
4 5
7.0%
5 5
7.0%
8 4
 
5.6%
, 4
 
5.6%
Other values (2) 3
 
4.2%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 15
Text

MISSING 

Distinct25
Distinct (%)75.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:45:15.252058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.2424242
Min length1

Characters and Unicode

Total characters74
Distinct characters15
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique22 ?
Unique (%)66.7%

Sample

1st row운암2동
2nd row6,087
3rd row11,743
4th row57
5th row8
ValueCountFrequency (%)
0 7
21.2%
36 2
 
6.1%
55 2
 
6.1%
8 2
 
6.1%
72 1
 
3.0%
87 1
 
3.0%
11,688 1
 
3.0%
6,080 1
 
3.0%
1 1
 
3.0%
7 1
 
3.0%
Other values (14) 14
42.4%
2024-02-10T09:45:15.986558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 11
14.9%
5 9
12.2%
8 8
10.8%
6 8
10.8%
1 8
10.8%
7 6
8.1%
3 5
6.8%
, 4
 
5.4%
2 4
 
5.4%
4 3
 
4.1%
Other values (5) 8
10.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 64
86.5%
Other Punctuation 4
 
5.4%
Dash Punctuation 3
 
4.1%
Other Letter 3
 
4.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 11
17.2%
5 9
14.1%
8 8
12.5%
6 8
12.5%
1 8
12.5%
7 6
9.4%
3 5
7.8%
2 4
 
6.2%
4 3
 
4.7%
9 2
 
3.1%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 71
95.9%
Hangul 3
 
4.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 11
15.5%
5 9
12.7%
8 8
11.3%
6 8
11.3%
1 8
11.3%
7 6
8.5%
3 5
7.0%
, 4
 
5.6%
2 4
 
5.6%
4 3
 
4.2%
Other values (2) 5
7.0%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 71
95.9%
Hangul 3
 
4.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 11
15.5%
5 9
12.7%
8 8
11.3%
6 8
11.3%
1 8
11.3%
7 6
8.5%
3 5
7.0%
, 4
 
5.6%
2 4
 
5.6%
4 3
 
4.2%
Other values (2) 5
7.0%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 16
Text

MISSING 

Distinct24
Distinct (%)72.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:45:16.337087image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.3939394
Min length1

Characters and Unicode

Total characters79
Distinct characters14
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique19 ?
Unique (%)57.6%

Sample

1st row운암3동
2nd row5,364
3rd row13,158
4th row29
5th row15
ValueCountFrequency (%)
0 6
18.2%
30 2
 
6.1%
101 2
 
6.1%
59 2
 
6.1%
15 2
 
6.1%
33 1
 
3.0%
61 1
 
3.0%
5,423 1
 
3.0%
1 1
 
3.0%
159 1
 
3.0%
Other values (14) 14
42.4%
2024-02-10T09:45:17.026197image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 17
21.5%
0 11
13.9%
5 11
13.9%
3 11
13.9%
9 5
 
6.3%
2 5
 
6.3%
, 4
 
5.1%
6 4
 
5.1%
4 4
 
5.1%
8 2
 
2.5%
Other values (4) 5
 
6.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 72
91.1%
Other Punctuation 4
 
5.1%
Other Letter 3
 
3.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 17
23.6%
0 11
15.3%
5 11
15.3%
3 11
15.3%
9 5
 
6.9%
2 5
 
6.9%
6 4
 
5.6%
4 4
 
5.6%
8 2
 
2.8%
7 2
 
2.8%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 76
96.2%
Hangul 3
 
3.8%

Most frequent character per script

Common
ValueCountFrequency (%)
1 17
22.4%
0 11
14.5%
5 11
14.5%
3 11
14.5%
9 5
 
6.6%
2 5
 
6.6%
, 4
 
5.3%
6 4
 
5.3%
4 4
 
5.3%
8 2
 
2.6%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 76
96.2%
Hangul 3
 
3.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 17
22.4%
0 11
14.5%
5 11
14.5%
3 11
14.5%
9 5
 
6.6%
2 5
 
6.6%
, 4
 
5.3%
6 4
 
5.3%
4 4
 
5.3%
8 2
 
2.6%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 17
Text

MISSING 

Distinct24
Distinct (%)72.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:45:17.362473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.3636364
Min length1

Characters and Unicode

Total characters78
Distinct characters14
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique21 ?
Unique (%)63.6%

Sample

1st row동림동
2nd row9,903
3rd row23,071
4th row53
5th row8
ValueCountFrequency (%)
0 8
24.2%
53 2
 
6.1%
8 2
 
6.1%
64 1
 
3.0%
23,071 1
 
3.0%
131 1
 
3.0%
9,918 1
 
3.0%
39 1
 
3.0%
15 1
 
3.0%
9 1
 
3.0%
Other values (14) 14
42.4%
2024-02-10T09:45:18.146690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 15
19.2%
1 12
15.4%
3 11
14.1%
9 7
9.0%
8 6
 
7.7%
2 6
 
7.7%
6 5
 
6.4%
, 4
 
5.1%
5 3
 
3.8%
7 3
 
3.8%
Other values (4) 6
 
7.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 70
89.7%
Other Punctuation 4
 
5.1%
Other Letter 3
 
3.8%
Dash Punctuation 1
 
1.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 15
21.4%
1 12
17.1%
3 11
15.7%
9 7
10.0%
8 6
 
8.6%
2 6
 
8.6%
6 5
 
7.1%
5 3
 
4.3%
7 3
 
4.3%
4 2
 
2.9%
Other Letter
ValueCountFrequency (%)
2
66.7%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 75
96.2%
Hangul 3
 
3.8%

Most frequent character per script

Common
ValueCountFrequency (%)
0 15
20.0%
1 12
16.0%
3 11
14.7%
9 7
9.3%
8 6
 
8.0%
2 6
 
8.0%
6 5
 
6.7%
, 4
 
5.3%
5 3
 
4.0%
7 3
 
4.0%
Other values (2) 3
 
4.0%
Hangul
ValueCountFrequency (%)
2
66.7%
1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 75
96.2%
Hangul 3
 
3.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 15
20.0%
1 12
16.0%
3 11
14.7%
9 7
9.3%
8 6
 
8.0%
2 6
 
8.0%
6 5
 
6.7%
, 4
 
5.3%
5 3
 
4.0%
7 3
 
4.0%
Other values (2) 3
 
4.0%
Hangul
ValueCountFrequency (%)
2
66.7%
1
33.3%

Unnamed: 18
Text

MISSING 

Distinct23
Distinct (%)69.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:45:18.424842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.1818182
Min length1

Characters and Unicode

Total characters72
Distinct characters15
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique18 ?
Unique (%)54.5%

Sample

1st row우산동
2nd row5,610
3rd row10,161
4th row61
5th row7
ValueCountFrequency (%)
0 7
21.2%
7 3
 
9.1%
26 2
 
6.1%
69 2
 
6.1%
1 2
 
6.1%
13 1
 
3.0%
61 1
 
3.0%
41 1
 
3.0%
10,102 1
 
3.0%
5,603 1
 
3.0%
Other values (12) 12
36.4%
2024-02-10T09:45:19.126422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 15
20.8%
0 12
16.7%
6 11
15.3%
2 6
 
8.3%
7 5
 
6.9%
9 4
 
5.6%
5 4
 
5.6%
, 4
 
5.6%
3 3
 
4.2%
4 2
 
2.8%
Other values (5) 6
 
8.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 63
87.5%
Other Punctuation 4
 
5.6%
Other Letter 3
 
4.2%
Dash Punctuation 2
 
2.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 15
23.8%
0 12
19.0%
6 11
17.5%
2 6
 
9.5%
7 5
 
7.9%
9 4
 
6.3%
5 4
 
6.3%
3 3
 
4.8%
4 2
 
3.2%
8 1
 
1.6%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 69
95.8%
Hangul 3
 
4.2%

Most frequent character per script

Common
ValueCountFrequency (%)
1 15
21.7%
0 12
17.4%
6 11
15.9%
2 6
 
8.7%
7 5
 
7.2%
9 4
 
5.8%
5 4
 
5.8%
, 4
 
5.8%
3 3
 
4.3%
4 2
 
2.9%
Other values (2) 3
 
4.3%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 69
95.8%
Hangul 3
 
4.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 15
21.7%
0 12
17.4%
6 11
15.9%
2 6
 
8.7%
7 5
 
7.2%
9 4
 
5.8%
5 4
 
5.8%
, 4
 
5.8%
3 3
 
4.3%
4 2
 
2.9%
Other values (2) 3
 
4.3%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 19
Text

MISSING 

Distinct26
Distinct (%)78.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:45:19.449680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
Mean length2.1212121
Min length1

Characters and Unicode

Total characters70
Distinct characters15
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique24 ?
Unique (%)72.7%

Sample

1st row풍향동
2nd row2,773
3rd row5,651
4th row23
5th row2
ValueCountFrequency (%)
0 6
18.2%
2 4
 
12.1%
1 2
 
6.1%
44 2
 
6.1%
58 1
 
3.0%
64 1
 
3.0%
5,607 1
 
3.0%
2,771 1
 
3.0%
17 1
 
3.0%
93 1
 
3.0%
Other values (13) 13
39.4%
2024-02-10T09:45:20.215014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 13
18.6%
1 9
12.9%
0 7
10.0%
7 7
10.0%
3 7
10.0%
4 6
8.6%
5 5
 
7.1%
, 4
 
5.7%
6 3
 
4.3%
- 3
 
4.3%
Other values (5) 6
8.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 60
85.7%
Other Punctuation 4
 
5.7%
Dash Punctuation 3
 
4.3%
Other Letter 3
 
4.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 13
21.7%
1 9
15.0%
0 7
11.7%
7 7
11.7%
3 7
11.7%
4 6
10.0%
5 5
 
8.3%
6 3
 
5.0%
8 2
 
3.3%
9 1
 
1.7%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 67
95.7%
Hangul 3
 
4.3%

Most frequent character per script

Common
ValueCountFrequency (%)
2 13
19.4%
1 9
13.4%
0 7
10.4%
7 7
10.4%
3 7
10.4%
4 6
9.0%
5 5
 
7.5%
, 4
 
6.0%
6 3
 
4.5%
- 3
 
4.5%
Other values (2) 3
 
4.5%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 67
95.7%
Hangul 3
 
4.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 13
19.4%
1 9
13.4%
0 7
10.4%
7 7
10.4%
3 7
10.4%
4 6
9.0%
5 5
 
7.5%
, 4
 
6.0%
6 3
 
4.5%
- 3
 
4.5%
Other values (2) 3
 
4.5%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 20
Text

MISSING 

Distinct28
Distinct (%)84.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:45:20.476587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.3636364
Min length1

Characters and Unicode

Total characters78
Distinct characters15
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique27 ?
Unique (%)81.8%

Sample

1st row문화동
2nd row9,695
3rd row20,619
4th row55
5th row7
ValueCountFrequency (%)
0 6
 
18.2%
7 2
 
6.1%
124 1
 
3.0%
250 1
 
3.0%
52 1
 
3.0%
20,526 1
 
3.0%
9,688 1
 
3.0%
3 1
 
3.0%
93 1
 
3.0%
16 1
 
3.0%
Other values (17) 17
51.5%
2024-02-10T09:45:21.239460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 10
12.8%
6 10
12.8%
1 9
11.5%
5 9
11.5%
2 8
10.3%
9 7
9.0%
7 5
6.4%
, 4
 
5.1%
3 4
 
5.1%
8 4
 
5.1%
Other values (5) 8
10.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 68
87.2%
Other Punctuation 4
 
5.1%
Dash Punctuation 3
 
3.8%
Other Letter 3
 
3.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 10
14.7%
6 10
14.7%
1 9
13.2%
5 9
13.2%
2 8
11.8%
9 7
10.3%
7 5
7.4%
3 4
 
5.9%
8 4
 
5.9%
4 2
 
2.9%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 75
96.2%
Hangul 3
 
3.8%

Most frequent character per script

Common
ValueCountFrequency (%)
0 10
13.3%
6 10
13.3%
1 9
12.0%
5 9
12.0%
2 8
10.7%
9 7
9.3%
7 5
6.7%
, 4
 
5.3%
3 4
 
5.3%
8 4
 
5.3%
Other values (2) 5
6.7%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 75
96.2%
Hangul 3
 
3.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 10
13.3%
6 10
13.3%
1 9
12.0%
5 9
12.0%
2 8
10.7%
9 7
9.3%
7 5
6.7%
, 4
 
5.3%
3 4
 
5.3%
8 4
 
5.3%
Other values (2) 5
6.7%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 21
Text

MISSING 

Distinct24
Distinct (%)72.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:45:21.538337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.1818182
Min length1

Characters and Unicode

Total characters72
Distinct characters15
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique21 ?
Unique (%)63.6%

Sample

1st row문흥1동
2nd row6,464
3rd row15,635
4th row27
5th row9
ValueCountFrequency (%)
0 8
24.2%
27 2
 
6.1%
9 2
 
6.1%
41 1
 
3.0%
15,635 1
 
3.0%
67 1
 
3.0%
6,465 1
 
3.0%
26 1
 
3.0%
1 1
 
3.0%
8 1
 
3.0%
Other values (14) 14
42.4%
2024-02-10T09:45:22.229060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6 11
15.3%
0 10
13.9%
1 9
12.5%
4 9
12.5%
5 7
9.7%
7 6
8.3%
2 4
 
5.6%
, 4
 
5.6%
9 3
 
4.2%
3 3
 
4.2%
Other values (5) 6
8.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 64
88.9%
Other Punctuation 4
 
5.6%
Other Letter 3
 
4.2%
Dash Punctuation 1
 
1.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
6 11
17.2%
0 10
15.6%
1 9
14.1%
4 9
14.1%
5 7
10.9%
7 6
9.4%
2 4
 
6.2%
9 3
 
4.7%
3 3
 
4.7%
8 2
 
3.1%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 69
95.8%
Hangul 3
 
4.2%

Most frequent character per script

Common
ValueCountFrequency (%)
6 11
15.9%
0 10
14.5%
1 9
13.0%
4 9
13.0%
5 7
10.1%
7 6
8.7%
2 4
 
5.8%
, 4
 
5.8%
9 3
 
4.3%
3 3
 
4.3%
Other values (2) 3
 
4.3%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 69
95.8%
Hangul 3
 
4.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6 11
15.9%
0 10
14.5%
1 9
13.0%
4 9
13.0%
5 7
10.1%
7 6
8.7%
2 4
 
5.8%
, 4
 
5.8%
9 3
 
4.3%
3 3
 
4.3%
Other values (2) 3
 
4.3%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 22
Text

MISSING 

Distinct24
Distinct (%)72.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:45:22.578437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.2424242
Min length1

Characters and Unicode

Total characters74
Distinct characters15
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique19 ?
Unique (%)57.6%

Sample

1st row문흥2동
2nd row7,375
3rd row15,471
4th row32
5th row4
ValueCountFrequency (%)
0 6
18.2%
4 2
 
6.1%
87 2
 
6.1%
1 2
 
6.1%
97 2
 
6.1%
82 1
 
3.0%
15,451 1
 
3.0%
7,386 1
 
3.0%
20 1
 
3.0%
11 1
 
3.0%
Other values (14) 14
42.4%
2024-02-10T09:45:23.228143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 12
16.2%
7 10
13.5%
0 8
10.8%
4 7
9.5%
5 7
9.5%
8 6
8.1%
3 6
8.1%
9 4
 
5.4%
, 4
 
5.4%
2 4
 
5.4%
Other values (5) 6
8.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 66
89.2%
Other Punctuation 4
 
5.4%
Other Letter 3
 
4.1%
Dash Punctuation 1
 
1.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 12
18.2%
7 10
15.2%
0 8
12.1%
4 7
10.6%
5 7
10.6%
8 6
9.1%
3 6
9.1%
9 4
 
6.1%
2 4
 
6.1%
6 2
 
3.0%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 71
95.9%
Hangul 3
 
4.1%

Most frequent character per script

Common
ValueCountFrequency (%)
1 12
16.9%
7 10
14.1%
0 8
11.3%
4 7
9.9%
5 7
9.9%
8 6
8.5%
3 6
8.5%
9 4
 
5.6%
, 4
 
5.6%
2 4
 
5.6%
Other values (2) 3
 
4.2%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 71
95.9%
Hangul 3
 
4.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 12
16.9%
7 10
14.1%
0 8
11.3%
4 7
9.9%
5 7
9.9%
8 6
8.5%
3 6
8.5%
9 4
 
5.6%
, 4
 
5.6%
2 4
 
5.6%
Other values (2) 3
 
4.2%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 23
Text

MISSING 

Distinct26
Distinct (%)78.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:45:23.553857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length2.1515152
Min length1

Characters and Unicode

Total characters71
Distinct characters15
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique24 ?
Unique (%)72.7%

Sample

1st row두암1동
2nd row4,013
3rd row7,662
4th row22
5th row8
ValueCountFrequency (%)
0 7
21.2%
2 2
 
6.1%
8 2
 
6.1%
64 1
 
3.0%
70 1
 
3.0%
7,624 1
 
3.0%
4,011 1
 
3.0%
1 1
 
3.0%
38 1
 
3.0%
5 1
 
3.0%
Other values (15) 15
45.5%
2024-02-10T09:45:24.381238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 12
16.9%
4 9
12.7%
2 9
12.7%
1 7
9.9%
3 7
9.9%
6 5
7.0%
, 4
 
5.6%
5 4
 
5.6%
8 3
 
4.2%
7 3
 
4.2%
Other values (5) 8
11.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 61
85.9%
Other Punctuation 4
 
5.6%
Dash Punctuation 3
 
4.2%
Other Letter 3
 
4.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 12
19.7%
4 9
14.8%
2 9
14.8%
1 7
11.5%
3 7
11.5%
6 5
8.2%
5 4
 
6.6%
8 3
 
4.9%
7 3
 
4.9%
9 2
 
3.3%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 68
95.8%
Hangul 3
 
4.2%

Most frequent character per script

Common
ValueCountFrequency (%)
0 12
17.6%
4 9
13.2%
2 9
13.2%
1 7
10.3%
3 7
10.3%
6 5
7.4%
, 4
 
5.9%
5 4
 
5.9%
8 3
 
4.4%
7 3
 
4.4%
Other values (2) 5
7.4%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 68
95.8%
Hangul 3
 
4.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 12
17.6%
4 9
13.2%
2 9
13.2%
1 7
10.3%
3 7
10.3%
6 5
7.4%
, 4
 
5.9%
5 4
 
5.9%
8 3
 
4.4%
7 3
 
4.4%
Other values (2) 5
7.4%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 24
Text

MISSING 

Distinct22
Distinct (%)66.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:45:24.664844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.2727273
Min length1

Characters and Unicode

Total characters75
Distinct characters15
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique16 ?
Unique (%)48.5%

Sample

1st row두암2동
2nd row7,685
3rd row15,817
4th row56
5th row9
ValueCountFrequency (%)
0 7
21.2%
7,685 2
 
6.1%
56 2
 
6.1%
9 2
 
6.1%
5 2
 
6.1%
1 2
 
6.1%
39 1
 
3.0%
83 1
 
3.0%
50 1
 
3.0%
111 1
 
3.0%
Other values (12) 12
36.4%
2024-02-10T09:45:25.684554image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 11
14.7%
0 10
13.3%
5 10
13.3%
7 7
9.3%
6 7
9.3%
3 6
8.0%
8 5
6.7%
2 5
6.7%
, 4
 
5.3%
9 4
 
5.3%
Other values (5) 6
8.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 67
89.3%
Other Punctuation 4
 
5.3%
Other Letter 3
 
4.0%
Dash Punctuation 1
 
1.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 11
16.4%
0 10
14.9%
5 10
14.9%
7 7
10.4%
6 7
10.4%
3 6
9.0%
8 5
7.5%
2 5
7.5%
9 4
 
6.0%
4 2
 
3.0%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 72
96.0%
Hangul 3
 
4.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 11
15.3%
0 10
13.9%
5 10
13.9%
7 7
9.7%
6 7
9.7%
3 6
8.3%
8 5
6.9%
2 5
6.9%
, 4
 
5.6%
9 4
 
5.6%
Other values (2) 3
 
4.2%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 72
96.0%
Hangul 3
 
4.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 11
15.3%
0 10
13.9%
5 10
13.9%
7 7
9.7%
6 7
9.7%
3 6
8.3%
8 5
6.9%
2 5
6.9%
, 4
 
5.6%
9 4
 
5.6%
Other values (2) 3
 
4.2%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 25
Text

MISSING 

Distinct21
Distinct (%)63.6%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:45:25.950987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.2424242
Min length1

Characters and Unicode

Total characters74
Distinct characters15
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique16 ?
Unique (%)48.5%

Sample

1st row두암3동
2nd row7,756
3rd row13,099
4th row46
5th row8
ValueCountFrequency (%)
0 9
27.3%
97 3
 
9.1%
8 2
 
6.1%
36 2
 
6.1%
46 2
 
6.1%
44 1
 
3.0%
177 1
 
3.0%
7,734 1
 
3.0%
22 1
 
3.0%
19 1
 
3.0%
Other values (10) 10
30.3%
2024-02-10T09:45:26.521559image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 13
17.6%
7 10
13.5%
9 8
10.8%
3 7
9.5%
4 6
8.1%
6 5
 
6.8%
2 5
 
6.8%
8 4
 
5.4%
, 4
 
5.4%
1 4
 
5.4%
Other values (5) 8
10.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 65
87.8%
Other Punctuation 4
 
5.4%
Other Letter 3
 
4.1%
Dash Punctuation 2
 
2.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 13
20.0%
7 10
15.4%
9 8
12.3%
3 7
10.8%
4 6
9.2%
6 5
 
7.7%
2 5
 
7.7%
8 4
 
6.2%
1 4
 
6.2%
5 3
 
4.6%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 71
95.9%
Hangul 3
 
4.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 13
18.3%
7 10
14.1%
9 8
11.3%
3 7
9.9%
4 6
8.5%
6 5
 
7.0%
2 5
 
7.0%
8 4
 
5.6%
, 4
 
5.6%
1 4
 
5.6%
Other values (2) 5
 
7.0%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 71
95.9%
Hangul 3
 
4.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 13
18.3%
7 10
14.1%
9 8
11.3%
3 7
9.9%
4 6
8.5%
6 5
 
7.0%
2 5
 
7.0%
8 4
 
5.6%
, 4
 
5.6%
1 4
 
5.6%
Other values (2) 5
 
7.0%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 26
Text

MISSING 

Distinct23
Distinct (%)69.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:45:26.870421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.1515152
Min length1

Characters and Unicode

Total characters71
Distinct characters15
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique18 ?
Unique (%)54.5%

Sample

1st row삼각동
2nd row6,053
3rd row13,826
4th row30
5th row4
ValueCountFrequency (%)
0 7
21.2%
5 2
 
6.1%
30 2
 
6.1%
4 2
 
6.1%
1 2
 
6.1%
6,053 1
 
3.0%
159 1
 
3.0%
6,054 1
 
3.0%
25 1
 
3.0%
42 1
 
3.0%
Other values (13) 13
39.4%
2024-02-10T09:45:27.643992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 12
16.9%
3 9
12.7%
1 8
11.3%
5 8
11.3%
4 6
8.5%
8 6
8.5%
6 5
7.0%
2 4
 
5.6%
, 4
 
5.6%
7 3
 
4.2%
Other values (5) 6
8.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 63
88.7%
Other Punctuation 4
 
5.6%
Other Letter 3
 
4.2%
Dash Punctuation 1
 
1.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 12
19.0%
3 9
14.3%
1 8
12.7%
5 8
12.7%
4 6
9.5%
8 6
9.5%
6 5
7.9%
2 4
 
6.3%
7 3
 
4.8%
9 2
 
3.2%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 68
95.8%
Hangul 3
 
4.2%

Most frequent character per script

Common
ValueCountFrequency (%)
0 12
17.6%
3 9
13.2%
1 8
11.8%
5 8
11.8%
4 6
8.8%
8 6
8.8%
6 5
7.4%
2 4
 
5.9%
, 4
 
5.9%
7 3
 
4.4%
Other values (2) 3
 
4.4%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 68
95.8%
Hangul 3
 
4.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 12
17.6%
3 9
13.2%
1 8
11.8%
5 8
11.8%
4 6
8.8%
8 6
8.8%
6 5
7.4%
2 4
 
5.9%
, 4
 
5.9%
7 3
 
4.4%
Other values (2) 3
 
4.4%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 27
Text

MISSING 

Distinct26
Distinct (%)78.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:45:27.980881image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length4
Mean length2.5151515
Min length1

Characters and Unicode

Total characters83
Distinct characters15
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique24 ?
Unique (%)72.7%

Sample

1st row일곡동
2nd row11,561
3rd row29,356
4th row34
5th row12
ValueCountFrequency (%)
0 7
21.2%
12 2
 
6.1%
172 1
 
3.0%
29,201 1
 
3.0%
11,541 1
 
3.0%
1 1
 
3.0%
155 1
 
3.0%
20 1
 
3.0%
8 1
 
3.0%
123 1
 
3.0%
Other values (16) 16
48.5%
2024-02-10T09:45:28.558499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 18
21.7%
0 10
12.0%
3 9
10.8%
2 8
9.6%
5 6
 
7.2%
6 6
 
7.2%
9 5
 
6.0%
4 5
 
6.0%
, 4
 
4.8%
7 4
 
4.8%
Other values (5) 8
9.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 73
88.0%
Other Punctuation 4
 
4.8%
Dash Punctuation 3
 
3.6%
Other Letter 3
 
3.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 18
24.7%
0 10
13.7%
3 9
12.3%
2 8
11.0%
5 6
 
8.2%
6 6
 
8.2%
9 5
 
6.8%
4 5
 
6.8%
7 4
 
5.5%
8 2
 
2.7%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 80
96.4%
Hangul 3
 
3.6%

Most frequent character per script

Common
ValueCountFrequency (%)
1 18
22.5%
0 10
12.5%
3 9
11.2%
2 8
10.0%
5 6
 
7.5%
6 6
 
7.5%
9 5
 
6.2%
4 5
 
6.2%
, 4
 
5.0%
7 4
 
5.0%
Other values (2) 5
 
6.2%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 80
96.4%
Hangul 3
 
3.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 18
22.5%
0 10
12.5%
3 9
11.2%
2 8
10.0%
5 6
 
7.5%
6 6
 
7.5%
9 5
 
6.2%
4 5
 
6.2%
, 4
 
5.0%
7 4
 
5.0%
Other values (2) 5
 
6.2%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 28
Text

MISSING 

Distinct25
Distinct (%)75.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:45:28.846316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.2424242
Min length1

Characters and Unicode

Total characters74
Distinct characters15
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique22 ?
Unique (%)66.7%

Sample

1st row매곡동
2nd row5,506
3rd row13,722
4th row24
5th row5
ValueCountFrequency (%)
0 7
21.2%
54 2
 
6.1%
5 2
 
6.1%
10 1
 
3.0%
87 1
 
3.0%
13,678 1
 
3.0%
5,503 1
 
3.0%
2 1
 
3.0%
44 1
 
3.0%
3 1
 
3.0%
Other values (15) 15
45.5%
2024-02-10T09:45:29.470810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 11
14.9%
5 11
14.9%
2 9
12.2%
1 8
10.8%
4 6
8.1%
3 5
6.8%
7 5
6.8%
, 4
 
5.4%
6 4
 
5.4%
8 3
 
4.1%
Other values (5) 8
10.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 64
86.5%
Other Punctuation 4
 
5.4%
Dash Punctuation 3
 
4.1%
Other Letter 3
 
4.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 11
17.2%
5 11
17.2%
2 9
14.1%
1 8
12.5%
4 6
9.4%
3 5
7.8%
7 5
7.8%
6 4
 
6.2%
8 3
 
4.7%
9 2
 
3.1%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 71
95.9%
Hangul 3
 
4.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 11
15.5%
5 11
15.5%
2 9
12.7%
1 8
11.3%
4 6
8.5%
3 5
7.0%
7 5
7.0%
, 4
 
5.6%
6 4
 
5.6%
8 3
 
4.2%
Other values (2) 5
7.0%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 71
95.9%
Hangul 3
 
4.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 11
15.5%
5 11
15.5%
2 9
12.7%
1 8
11.3%
4 6
8.5%
3 5
7.0%
7 5
7.0%
, 4
 
5.6%
6 4
 
5.6%
8 3
 
4.2%
Other values (2) 5
7.0%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 29
Text

MISSING 

Distinct27
Distinct (%)81.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:45:29.819752image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.2121212
Min length1

Characters and Unicode

Total characters73
Distinct characters15
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique24 ?
Unique (%)72.7%

Sample

1st row오치1동
2nd row5,475
3rd row10,674
4th row44
5th row8
ValueCountFrequency (%)
0 5
 
15.2%
2 2
 
6.1%
58 2
 
6.1%
8 2
 
6.1%
86 1
 
3.0%
44 1
 
3.0%
10,674 1
 
3.0%
10,616 1
 
3.0%
5,477 1
 
3.0%
4 1
 
3.0%
Other values (16) 16
48.5%
2024-02-10T09:45:30.439562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4 10
13.7%
0 8
11.0%
2 8
11.0%
1 8
11.0%
6 8
11.0%
8 7
9.6%
5 7
9.6%
7 5
6.8%
, 4
 
5.5%
3 2
 
2.7%
Other values (5) 6
8.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 64
87.7%
Other Punctuation 4
 
5.5%
Other Letter 3
 
4.1%
Dash Punctuation 2
 
2.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 10
15.6%
0 8
12.5%
2 8
12.5%
1 8
12.5%
6 8
12.5%
8 7
10.9%
5 7
10.9%
7 5
7.8%
3 2
 
3.1%
9 1
 
1.6%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 70
95.9%
Hangul 3
 
4.1%

Most frequent character per script

Common
ValueCountFrequency (%)
4 10
14.3%
0 8
11.4%
2 8
11.4%
1 8
11.4%
6 8
11.4%
8 7
10.0%
5 7
10.0%
7 5
7.1%
, 4
 
5.7%
3 2
 
2.9%
Other values (2) 3
 
4.3%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 70
95.9%
Hangul 3
 
4.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4 10
14.3%
0 8
11.4%
2 8
11.4%
1 8
11.4%
6 8
11.4%
8 7
10.0%
5 7
10.0%
7 5
7.1%
, 4
 
5.7%
3 2
 
2.9%
Other values (2) 3
 
4.3%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 30
Text

MISSING 

Distinct27
Distinct (%)81.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:45:30.723395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.3636364
Min length1

Characters and Unicode

Total characters78
Distinct characters15
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique25 ?
Unique (%)75.8%

Sample

1st row오치2동
2nd row6,977
3rd row12,288
4th row44
5th row10
ValueCountFrequency (%)
0 6
 
18.2%
15 2
 
6.1%
69 2
 
6.1%
10 2
 
6.1%
오치2동 1
 
3.0%
93 1
 
3.0%
12,219 1
 
3.0%
6,962 1
 
3.0%
4 1
 
3.0%
1 1
 
3.0%
Other values (15) 15
45.5%
2024-02-10T09:45:31.540477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 11
14.1%
1 10
12.8%
2 9
11.5%
6 7
9.0%
9 7
9.0%
4 7
9.0%
8 5
6.4%
, 4
 
5.1%
7 4
 
5.1%
5 4
 
5.1%
Other values (5) 10
12.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 68
87.2%
Other Punctuation 4
 
5.1%
Dash Punctuation 3
 
3.8%
Other Letter 3
 
3.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 11
16.2%
1 10
14.7%
2 9
13.2%
6 7
10.3%
9 7
10.3%
4 7
10.3%
8 5
7.4%
7 4
 
5.9%
5 4
 
5.9%
3 4
 
5.9%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 75
96.2%
Hangul 3
 
3.8%

Most frequent character per script

Common
ValueCountFrequency (%)
0 11
14.7%
1 10
13.3%
2 9
12.0%
6 7
9.3%
9 7
9.3%
4 7
9.3%
8 5
6.7%
, 4
 
5.3%
7 4
 
5.3%
5 4
 
5.3%
Other values (2) 7
9.3%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 75
96.2%
Hangul 3
 
3.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 11
14.7%
1 10
13.3%
2 9
12.0%
6 7
9.3%
9 7
9.3%
4 7
9.3%
8 5
6.7%
, 4
 
5.3%
7 4
 
5.3%
5 4
 
5.3%
Other values (2) 7
9.3%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 31
Text

MISSING 

Distinct21
Distinct (%)63.6%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:45:31.884965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length1
Mean length1.8787879
Min length1

Characters and Unicode

Total characters62
Distinct characters14
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique14 ?
Unique (%)42.4%

Sample

1st row석곡동
2nd row1,381
3rd row2,482
4th row22
5th row3
ValueCountFrequency (%)
0 7
21.2%
2 3
 
9.1%
11 2
 
6.1%
1 2
 
6.1%
3 2
 
6.1%
22 2
 
6.1%
7 2
 
6.1%
12 1
 
3.0%
21 1
 
3.0%
14 1
 
3.0%
Other values (10) 10
30.3%
2024-02-10T09:45:32.801203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 13
21.0%
1 13
21.0%
0 8
12.9%
3 5
 
8.1%
7 4
 
6.5%
, 4
 
6.5%
4 4
 
6.5%
8 4
 
6.5%
- 2
 
3.2%
9 1
 
1.6%
Other values (4) 4
 
6.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 53
85.5%
Other Punctuation 4
 
6.5%
Other Letter 3
 
4.8%
Dash Punctuation 2
 
3.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 13
24.5%
1 13
24.5%
0 8
15.1%
3 5
 
9.4%
7 4
 
7.5%
4 4
 
7.5%
8 4
 
7.5%
9 1
 
1.9%
6 1
 
1.9%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 59
95.2%
Hangul 3
 
4.8%

Most frequent character per script

Common
ValueCountFrequency (%)
2 13
22.0%
1 13
22.0%
0 8
13.6%
3 5
 
8.5%
7 4
 
6.8%
, 4
 
6.8%
4 4
 
6.8%
8 4
 
6.8%
- 2
 
3.4%
9 1
 
1.7%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 59
95.2%
Hangul 3
 
4.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 13
22.0%
1 13
22.0%
0 8
13.6%
3 5
 
8.5%
7 4
 
6.8%
, 4
 
6.8%
4 4
 
6.8%
8 4
 
6.8%
- 2
 
3.4%
9 1
 
1.7%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 32
Text

MISSING 

Distinct25
Distinct (%)75.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:45:33.214511image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.3939394
Min length1

Characters and Unicode

Total characters79
Distinct characters15
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique22 ?
Unique (%)66.7%

Sample

1st row건국동
2nd row9,110
3rd row21,985
4th row61
5th row9
ValueCountFrequency (%)
0 7
21.2%
9 2
 
6.1%
61 2
 
6.1%
18 1
 
3.0%
130 1
 
3.0%
9,085 1
 
3.0%
53 1
 
3.0%
25 1
 
3.0%
1 1
 
3.0%
10 1
 
3.0%
Other values (15) 15
45.5%
2024-02-10T09:45:33.998442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 18
22.8%
0 14
17.7%
8 9
11.4%
9 6
 
7.6%
2 6
 
7.6%
5 6
 
7.6%
6 4
 
5.1%
, 4
 
5.1%
7 3
 
3.8%
3 3
 
3.8%
Other values (5) 6
 
7.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 70
88.6%
Other Punctuation 4
 
5.1%
Other Letter 3
 
3.8%
Dash Punctuation 2
 
2.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 18
25.7%
0 14
20.0%
8 9
12.9%
9 6
 
8.6%
2 6
 
8.6%
5 6
 
8.6%
6 4
 
5.7%
7 3
 
4.3%
3 3
 
4.3%
4 1
 
1.4%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 76
96.2%
Hangul 3
 
3.8%

Most frequent character per script

Common
ValueCountFrequency (%)
1 18
23.7%
0 14
18.4%
8 9
11.8%
9 6
 
7.9%
2 6
 
7.9%
5 6
 
7.9%
6 4
 
5.3%
, 4
 
5.3%
7 3
 
3.9%
3 3
 
3.9%
Other values (2) 3
 
3.9%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 76
96.2%
Hangul 3
 
3.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 18
23.7%
0 14
18.4%
8 9
11.8%
9 6
 
7.9%
2 6
 
7.9%
5 6
 
7.9%
6 4
 
5.3%
, 4
 
5.3%
7 3
 
3.9%
3 3
 
3.9%
Other values (2) 3
 
3.9%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 33
Text

MISSING 

Distinct27
Distinct (%)81.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:45:34.393089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length4
Mean length2.6969697
Min length1

Characters and Unicode

Total characters89
Distinct characters15
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique25 ?
Unique (%)75.8%

Sample

1st row양산동
2nd row16,370
3rd row37,396
4th row60
5th row18
ValueCountFrequency (%)
0 6
 
18.2%
18 2
 
6.1%
255 1
 
3.0%
494 1
 
3.0%
64 1
 
3.0%
37,226 1
 
3.0%
16,340 1
 
3.0%
4 1
 
3.0%
170 1
 
3.0%
30 1
 
3.0%
Other values (17) 17
51.5%
2024-02-10T09:45:35.434920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 14
15.7%
0 13
14.6%
3 11
12.4%
6 9
10.1%
7 7
7.9%
2 7
7.9%
4 6
6.7%
5 5
 
5.6%
8 4
 
4.5%
, 4
 
4.5%
Other values (5) 9
10.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 80
89.9%
Other Punctuation 4
 
4.5%
Other Letter 3
 
3.4%
Dash Punctuation 2
 
2.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 14
17.5%
0 13
16.2%
3 11
13.8%
6 9
11.2%
7 7
8.8%
2 7
8.8%
4 6
7.5%
5 5
 
6.2%
8 4
 
5.0%
9 4
 
5.0%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 86
96.6%
Hangul 3
 
3.4%

Most frequent character per script

Common
ValueCountFrequency (%)
1 14
16.3%
0 13
15.1%
3 11
12.8%
6 9
10.5%
7 7
8.1%
2 7
8.1%
4 6
7.0%
5 5
 
5.8%
8 4
 
4.7%
, 4
 
4.7%
Other values (2) 6
7.0%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 86
96.6%
Hangul 3
 
3.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 14
16.3%
0 13
15.1%
3 11
12.8%
6 9
10.5%
7 7
8.1%
2 7
8.1%
4 6
7.0%
5 5
 
5.8%
8 4
 
4.7%
, 4
 
4.7%
Other values (2) 6
7.0%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 34
Text

MISSING 

Distinct24
Distinct (%)72.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:45:35.784967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length3
Mean length2.3636364
Min length1

Characters and Unicode

Total characters78
Distinct characters15
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique22 ?
Unique (%)66.7%

Sample

1st row신용동
2nd row11,814
3rd row29,527
4th row8
5th row9
ValueCountFrequency (%)
0 7
21.2%
9 4
 
12.1%
29,527 1
 
3.0%
8 1
 
3.0%
11,829 1
 
3.0%
1 1
 
3.0%
64 1
 
3.0%
15 1
 
3.0%
83 1
 
3.0%
148 1
 
3.0%
Other values (14) 14
42.4%
2024-02-10T09:45:36.435318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 14
17.9%
0 10
12.8%
7 10
12.8%
9 8
10.3%
2 7
9.0%
3 5
 
6.4%
8 5
 
6.4%
4 5
 
6.4%
, 4
 
5.1%
5 3
 
3.8%
Other values (5) 7
9.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 70
89.7%
Other Punctuation 4
 
5.1%
Other Letter 3
 
3.8%
Dash Punctuation 1
 
1.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 14
20.0%
0 10
14.3%
7 10
14.3%
9 8
11.4%
2 7
10.0%
3 5
 
7.1%
8 5
 
7.1%
4 5
 
7.1%
5 3
 
4.3%
6 3
 
4.3%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 75
96.2%
Hangul 3
 
3.8%

Most frequent character per script

Common
ValueCountFrequency (%)
1 14
18.7%
0 10
13.3%
7 10
13.3%
9 8
10.7%
2 7
9.3%
3 5
 
6.7%
8 5
 
6.7%
4 5
 
6.7%
, 4
 
5.3%
5 3
 
4.0%
Other values (2) 4
 
5.3%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 75
96.2%
Hangul 3
 
3.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 14
18.7%
0 10
13.3%
7 10
13.3%
9 8
10.7%
2 7
9.3%
3 5
 
6.7%
8 5
 
6.7%
4 5
 
6.7%
, 4
 
5.3%
5 3
 
4.0%
Other values (2) 4
 
5.3%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Sample

Unnamed: 0인구이동보고서(1호)Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 6Unnamed: 7Unnamed: 8Unnamed: 9Unnamed: 10Unnamed: 11Unnamed: 12Unnamed: 13Unnamed: 14Unnamed: 15Unnamed: 16Unnamed: 17Unnamed: 18Unnamed: 19Unnamed: 20Unnamed: 21Unnamed: 22Unnamed: 23Unnamed: 24Unnamed: 25Unnamed: 26Unnamed: 27Unnamed: 28Unnamed: 29Unnamed: 30Unnamed: 31Unnamed: 32Unnamed: 33Unnamed: 34
0<NA>행정기관 :<NA>광주광역시 북구<NA><NA><NA><NA><NA><NA>출력일자 :<NA>2022.09.13<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
1<NA>작성기준 :<NA>2022.08 현재<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
2<NA>시, 군, 구(읍면동)<NA><NA><NA>합 계중흥1동중흥2동중흥3동중앙동임동신안동<NA>용봉동운암1동운암2동운암3동동림동우산동풍향동문화동문흥1동문흥2동두암1동두암2동두암3동삼각동일곡동매곡동오치1동오치2동석곡동건국동양산동신용동
3<NA>전월말세대수<NA><NA><NA>197,5422,9974,4493,5982,4074,5767,233<NA>17,8477,4636,0875,3649,9035,6102,7739,6956,4647,3754,0137,6857,7566,05311,5615,5065,4756,9771,3819,11016,37011,814
4<NA>전월말인구수<NA><NA><NA>425,8814,7238,5326,5304,0549,15912,353<NA>38,04719,14011,74313,15823,07110,1615,65120,61915,63515,4717,66215,81713,09913,82629,35613,72210,67412,2882,48221,98537,39629,527
5<NA>전월말거주불명자수<NA><NA><NA>1,270546142493788<NA>12427572953612355273222564630342444442261608
6<NA>전월말재외국민등록자수<NA><NA><NA>221063452<NA>2018815872794898412581039189
7<NA>증 가 요 인전 입<NA>4,206341631417665172<NA>4641431102612186978155116174991509913317911212210721188326231
8<NA><NA><NA>남자<NA>2,148147975383397<NA>2426865125110413476668744875275945864581488157107
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Unnamed: 0인구이동보고서(1호)Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 6Unnamed: 7Unnamed: 8Unnamed: 9Unnamed: 10Unnamed: 11Unnamed: 12Unnamed: 13Unnamed: 14Unnamed: 15Unnamed: 16Unnamed: 17Unnamed: 18Unnamed: 19Unnamed: 20Unnamed: 21Unnamed: 22Unnamed: 23Unnamed: 24Unnamed: 25Unnamed: 26Unnamed: 27Unnamed: 28Unnamed: 29Unnamed: 30Unnamed: 31Unnamed: 32Unnamed: 33Unnamed: 34
25<NA><NA>말소<NA><NA>10000001<NA>3000001000010000111100
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27<NA><NA>기타<NA><NA>0000000<NA>0000000000000000000000
28<NA>세대수증감<NA><NA><NA>14-231428-18-215<NA>353-75915-7-2-7111-20-221-20-32-15-2-25-3015
29<NA>인구수증감<NA><NA><NA>-1,166-491649-9-340<NA>-61-41-55159-39-59-44-93-26-20-38-83-97-25-155-44-58-69-4-53-170-64
30<NA>거주불명자수증감<NA><NA><NA>-2-11101-1-2<NA>-10-1101-1-301-1000-1-2-4-40041
31<NA>금월말세대수<NA><NA><NA>197,5562,9744,4633,6262,3894,5747,248<NA>17,8827,4666,0805,4239,9185,6032,7719,6886,4657,3864,0117,6857,7346,05411,5415,5035,4776,9621,3799,08516,34011,829
32<NA>금월말인구수<NA><NA><NA>424,7154,6748,5486,5794,0459,12512,353<NA>37,98619,09911,68813,31723,03210,1025,60720,52615,60915,4517,62415,73413,00213,80129,20113,67810,61612,2192,47821,93237,22629,463
33<NA>금월말거주불명자수<NA><NA><NA>1,268536252503686<NA>12327563053622252273321564630332240402261649
34<NA>금월말재외국민등록자수<NA><NA><NA>220063451<NA>2018815872894898412581039179

Duplicate rows

Most frequently occurring

인구이동보고서(1호)Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 6Unnamed: 7Unnamed: 8Unnamed: 9Unnamed: 10Unnamed: 11Unnamed: 12Unnamed: 13Unnamed: 14Unnamed: 15Unnamed: 16Unnamed: 17Unnamed: 18Unnamed: 19Unnamed: 20Unnamed: 21Unnamed: 22Unnamed: 23Unnamed: 24Unnamed: 25Unnamed: 26Unnamed: 27Unnamed: 28Unnamed: 29Unnamed: 30Unnamed: 31Unnamed: 32Unnamed: 33Unnamed: 34# duplicates
0<NA>국외<NA><NA>0000000<NA>00000000000000000000002
1<NA>기타<NA><NA>0000000<NA>00000000000000000000002