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

Description2022-06-15
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 09:42:33.587935
Analysis finished2024-02-10 09:42:35.676629
Duration2.09 seconds
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
2024-02-10T09:42:36.031715image/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%
2024-02-10T09:42:37.197094image/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
2024-02-10T09:42:37.675213image/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%
2024-02-10T09:42:38.673002image/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
2024-02-10T09:42:39.136227image/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 row2022.05 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%
2022.05 1
7.1%
현재 1
7.1%
2024-02-10T09:42:40.110234image/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%
5 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%
5 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%
5 1
 
10.0%
. 1
 
10.0%

Unnamed: 4
Text

MISSING 

Distinct2
Distinct (%)50.0%
Missing31
Missing (%)88.6%
Memory size412.0 B
2024-02-10T09:42:40.458814image/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%
2024-02-10T09:42:41.340478image/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 

Distinct26
Distinct (%)78.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:42:41.897828image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length4
Min length1

Characters and Unicode

Total characters132
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

Unique22 ?
Unique (%)66.7%

Sample

1st row합 계
2nd row196,995
3rd row426,745
4th row1,268
5th row222
ValueCountFrequency (%)
0 5
 
14.7%
10 2
 
5.9%
1,621 2
 
5.9%
222 2
 
5.9%
2,251 1
 
2.9%
4,498 1
 
2.9%
426,329 1
 
2.9%
197,158 1
 
2.9%
416 1
 
2.9%
163 1
 
2.9%
Other values (17) 17
50.0%
2024-02-10T09:42:43.270321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 24
18.2%
1 22
16.7%
, 18
13.6%
4 12
9.1%
0 10
7.6%
9 10
7.6%
6 9
 
6.8%
3 8
 
6.1%
5 5
 
3.8%
8 5
 
3.8%
Other values (5) 9
 
6.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 109
82.6%
Other Punctuation 18
 
13.6%
Space Separator 2
 
1.5%
Other Letter 2
 
1.5%
Dash Punctuation 1
 
0.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 24
22.0%
1 22
20.2%
4 12
11.0%
0 10
9.2%
9 10
9.2%
6 9
 
8.3%
3 8
 
7.3%
5 5
 
4.6%
8 5
 
4.6%
7 4
 
3.7%
Other Letter
ValueCountFrequency (%)
1
50.0%
1
50.0%
Other Punctuation
ValueCountFrequency (%)
, 18
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 130
98.5%
Hangul 2
 
1.5%

Most frequent character per script

Common
ValueCountFrequency (%)
2 24
18.5%
1 22
16.9%
, 18
13.8%
4 12
9.2%
0 10
7.7%
9 10
7.7%
6 9
 
6.9%
3 8
 
6.2%
5 5
 
3.8%
8 5
 
3.8%
Other values (3) 7
 
5.4%
Hangul
ValueCountFrequency (%)
1
50.0%
1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 130
98.5%
Hangul 2
 
1.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 24
18.5%
1 22
16.9%
, 18
13.8%
4 12
9.2%
0 10
7.7%
9 10
7.7%
6 9
 
6.9%
3 8
 
6.2%
5 5
 
3.8%
8 5
 
3.8%
Other values (3) 7
 
5.4%
Hangul
ValueCountFrequency (%)
1
50.0%
1
50.0%

Unnamed: 6
Text

MISSING 

Distinct24
Distinct (%)72.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:42:43.618391image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
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

Unique21 ?
Unique (%)63.6%

Sample

1st row중흥1동
2nd row3,006
3rd row4,753
4th row57
5th row0
ValueCountFrequency (%)
0 8
24.2%
23 2
 
6.1%
2 2
 
6.1%
55 2
 
6.1%
14 1
 
3.0%
40 1
 
3.0%
3,002 1
 
3.0%
26 1
 
3.0%
4 1
 
3.0%
1 1
 
3.0%
Other values (13) 13
39.4%
2024-02-10T09:42:44.555083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 13
18.6%
2 10
14.3%
4 9
12.9%
3 7
10.0%
1 7
10.0%
5 6
8.6%
, 4
 
5.7%
7 4
 
5.7%
- 3
 
4.3%
6 2
 
2.9%
Other values (5) 5
 
7.1%

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 (%)
0 13
21.7%
2 10
16.7%
4 9
15.0%
3 7
11.7%
1 7
11.7%
5 6
10.0%
7 4
 
6.7%
6 2
 
3.3%
9 1
 
1.7%
8 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 (%)
0 13
19.4%
2 10
14.9%
4 9
13.4%
3 7
10.4%
1 7
10.4%
5 6
9.0%
, 4
 
6.0%
7 4
 
6.0%
- 3
 
4.5%
6 2
 
3.0%
Other values (2) 2
 
3.0%
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 (%)
0 13
19.4%
2 10
14.9%
4 9
13.4%
3 7
10.4%
1 7
10.4%
5 6
9.0%
, 4
 
6.0%
7 4
 
6.0%
- 3
 
4.5%
6 2
 
3.0%
Other values (2) 2
 
3.0%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 7
Text

MISSING 

Distinct25
Distinct (%)75.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:42:44.944453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
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

Unique22 ?
Unique (%)66.7%

Sample

1st row중흥2동
2nd row4,340
3rd row8,323
4th row63
5th row6
ValueCountFrequency (%)
0 7
21.2%
62 2
 
6.1%
6 2
 
6.1%
3 1
 
3.0%
108 1
 
3.0%
4,407 1
 
3.0%
1 1
 
3.0%
138 1
 
3.0%
67 1
 
3.0%
8 1
 
3.0%
Other values (15) 15
45.5%
2024-02-10T09:42:46.024565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 11
14.7%
6 9
12.0%
4 9
12.0%
3 9
12.0%
1 9
12.0%
2 7
9.3%
8 5
6.7%
, 4
 
5.3%
5 3
 
4.0%
7 3
 
4.0%
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 (%)
0 11
16.4%
6 9
13.4%
4 9
13.4%
3 9
13.4%
1 9
13.4%
2 7
10.4%
8 5
7.5%
5 3
 
4.5%
7 3
 
4.5%
9 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 (%)
0 11
15.3%
6 9
12.5%
4 9
12.5%
3 9
12.5%
1 9
12.5%
2 7
9.7%
8 5
6.9%
, 4
 
5.6%
5 3
 
4.2%
7 3
 
4.2%
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 (%)
0 11
15.3%
6 9
12.5%
4 9
12.5%
3 9
12.5%
1 9
12.5%
2 7
9.7%
8 5
6.9%
, 4
 
5.6%
5 3
 
4.2%
7 3
 
4.2%
Other values (2) 3
 
4.2%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 8
Text

MISSING 

Distinct23
Distinct (%)69.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:42:46.411645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length2.2121212
Min length1

Characters and Unicode

Total characters73
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 row중흥3동
2nd row3,370
3rd row6,145
4th row42
5th row3
ValueCountFrequency (%)
0 8
24.2%
3 2
 
6.1%
42 2
 
6.1%
37 2
 
6.1%
23 1
 
3.0%
6,145 1
 
3.0%
3,370 1
 
3.0%
3,458 1
 
3.0%
179 1
 
3.0%
88 1
 
3.0%
Other values (13) 13
39.4%
2024-02-10T09:42:47.355508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 12
16.4%
0 9
12.3%
4 9
12.3%
1 9
12.3%
7 7
9.6%
2 7
9.6%
8 4
 
5.5%
5 4
 
5.5%
, 4
 
5.5%
6 3
 
4.1%
Other values (4) 5
6.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 66
90.4%
Other Punctuation 4
 
5.5%
Other Letter 3
 
4.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 12
18.2%
0 9
13.6%
4 9
13.6%
1 9
13.6%
7 7
10.6%
2 7
10.6%
8 4
 
6.1%
5 4
 
6.1%
6 3
 
4.5%
9 2
 
3.0%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
3 12
17.1%
0 9
12.9%
4 9
12.9%
1 9
12.9%
7 7
10.0%
2 7
10.0%
8 4
 
5.7%
5 4
 
5.7%
, 4
 
5.7%
6 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 (%)
3 12
17.1%
0 9
12.9%
4 9
12.9%
1 9
12.9%
7 7
10.0%
2 7
10.0%
8 4
 
5.7%
5 4
 
5.7%
, 4
 
5.7%
6 3
 
4.3%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 9
Text

MISSING 

Distinct22
Distinct (%)66.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:42:47.749640image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
Mean length2.1515152
Min length1

Characters and Unicode

Total characters71
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

Unique18 ?
Unique (%)54.5%

Sample

1st row중앙동
2nd row2,337
3rd row3,865
4th row51
5th row4
ValueCountFrequency (%)
0 8
24.2%
4 3
 
9.1%
51 2
 
6.1%
49 2
 
6.1%
22 1
 
3.0%
5 1
 
3.0%
2,379 1
 
3.0%
117 1
 
3.0%
42 1
 
3.0%
18 1
 
3.0%
Other values (12) 12
36.4%
2024-02-10T09:42:48.820387image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 11
15.5%
1 9
12.7%
2 8
11.3%
4 7
9.9%
5 7
9.9%
3 6
8.5%
9 5
7.0%
, 4
 
5.6%
7 4
 
5.6%
8 4
 
5.6%
Other values (4) 6
8.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 64
90.1%
Other Punctuation 4
 
5.6%
Other Letter 3
 
4.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 11
17.2%
1 9
14.1%
2 8
12.5%
4 7
10.9%
5 7
10.9%
3 6
9.4%
9 5
7.8%
7 4
 
6.2%
8 4
 
6.2%
6 3
 
4.7%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
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 9
13.2%
2 8
11.8%
4 7
10.3%
5 7
10.3%
3 6
8.8%
9 5
7.4%
, 4
 
5.9%
7 4
 
5.9%
8 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 (%)
0 11
16.2%
1 9
13.2%
2 8
11.8%
4 7
10.3%
5 7
10.3%
3 6
8.8%
9 5
7.4%
, 4
 
5.9%
7 4
 
5.9%
8 4
 
5.9%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 10
Text

MISSING 

Distinct21
Distinct (%)61.8%
Missing1
Missing (%)2.9%
Memory size412.0 B
2024-02-10T09:42:49.219932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.1470588
Min length1

Characters and Unicode

Total characters73
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

Unique15 ?
Unique (%)44.1%

Sample

1st row출력일자 :
2nd row임동
3rd row4,548
4th row9,190
5th row38
ValueCountFrequency (%)
0 8
22.9%
5 3
 
8.6%
43 2
 
5.7%
38 2
 
5.7%
42 2
 
5.7%
7 2
 
5.7%
24 2
 
5.7%
17 1
 
2.9%
4,555 1
 
2.9%
53 1
 
2.9%
Other values (11) 11
31.4%
2024-02-10T09:42:50.086868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 10
13.7%
4 10
13.7%
5 9
12.3%
3 7
9.6%
1 5
6.8%
2 5
6.8%
, 4
 
5.5%
9 4
 
5.5%
8 4
 
5.5%
7 3
 
4.1%
Other values (10) 12
16.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 60
82.2%
Other Letter 6
 
8.2%
Other Punctuation 5
 
6.8%
Space Separator 1
 
1.4%
Dash Punctuation 1
 
1.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 10
16.7%
4 10
16.7%
5 9
15.0%
3 7
11.7%
1 5
8.3%
2 5
8.3%
9 4
 
6.7%
8 4
 
6.7%
7 3
 
5.0%
6 3
 
5.0%
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%
Space Separator
ValueCountFrequency (%)
1
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 67
91.8%
Hangul 6
 
8.2%

Most frequent character per script

Common
ValueCountFrequency (%)
0 10
14.9%
4 10
14.9%
5 9
13.4%
3 7
10.4%
1 5
7.5%
2 5
7.5%
, 4
 
6.0%
9 4
 
6.0%
8 4
 
6.0%
7 3
 
4.5%
Other values (4) 6
9.0%
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 67
91.8%
Hangul 6
 
8.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 10
14.9%
4 10
14.9%
5 9
13.4%
3 7
10.4%
1 5
7.5%
2 5
7.5%
, 4
 
6.0%
9 4
 
6.0%
8 4
 
6.0%
7 3
 
4.5%
Other values (4) 6
9.0%
Hangul
ValueCountFrequency (%)
1
16.7%
1
16.7%
1
16.7%
1
16.7%
1
16.7%
1
16.7%

Unnamed: 11
Text

MISSING 

Distinct26
Distinct (%)78.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:42:50.686149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.1818182
Min length1

Characters and Unicode

Total characters72
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

Unique23 ?
Unique (%)69.7%

Sample

1st row신안동
2nd row7,209
3rd row12,346
4th row84
5th row2
ValueCountFrequency (%)
0 6
 
18.2%
47 2
 
6.1%
2 2
 
6.1%
61 1
 
3.0%
78 1
 
3.0%
12,393 1
 
3.0%
7,244 1
 
3.0%
6 1
 
3.0%
35 1
 
3.0%
1 1
 
3.0%
Other values (16) 16
48.5%
2024-02-10T09:42:51.438990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4 10
13.9%
0 9
12.5%
1 8
11.1%
8 7
9.7%
2 6
8.3%
7 6
8.3%
9 6
8.3%
3 5
6.9%
, 4
 
5.6%
6 4
 
5.6%
Other values (4) 7
9.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 65
90.3%
Other Punctuation 4
 
5.6%
Other Letter 3
 
4.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 10
15.4%
0 9
13.8%
1 8
12.3%
8 7
10.8%
2 6
9.2%
7 6
9.2%
9 6
9.2%
3 5
7.7%
6 4
 
6.2%
5 4
 
6.2%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
4 10
14.5%
0 9
13.0%
1 8
11.6%
8 7
10.1%
2 6
8.7%
7 6
8.7%
9 6
8.7%
3 5
7.2%
, 4
 
5.8%
6 4
 
5.8%
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 (%)
4 10
14.5%
0 9
13.0%
1 8
11.6%
8 7
10.1%
2 6
8.7%
7 6
8.7%
9 6
8.7%
3 5
7.2%
, 4
 
5.8%
6 4
 
5.8%
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
Minimum2022-06-13 00:00:00
Maximum2022-06-13 00:00:00
2024-02-10T09:42:51.761037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-10T09:42:52.184966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Unnamed: 13
Text

MISSING 

Distinct27
Distinct (%)81.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:42:52.519513image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length4
Mean length2.7878788
Min length1

Characters and Unicode

Total characters92
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

Unique24 ?
Unique (%)72.7%

Sample

1st row용봉동
2nd row17,887
3rd row38,309
4th row123
5th row19
ValueCountFrequency (%)
0 5
 
15.2%
2 2
 
6.1%
162 2
 
6.1%
448 1
 
3.0%
220 1
 
3.0%
120 1
 
3.0%
38,187 1
 
3.0%
17,847 1
 
3.0%
3 1
 
3.0%
122 1
 
3.0%
Other values (17) 17
51.5%
2024-02-10T09:42:53.486638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 17
18.5%
2 15
16.3%
0 11
12.0%
8 9
9.8%
6 8
8.7%
7 7
7.6%
3 6
 
6.5%
4 5
 
5.4%
, 4
 
4.3%
9 4
 
4.3%
Other values (4) 6
 
6.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 82
89.1%
Other Punctuation 4
 
4.3%
Dash Punctuation 3
 
3.3%
Other Letter 3
 
3.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 17
20.7%
2 15
18.3%
0 11
13.4%
8 9
11.0%
6 8
9.8%
7 7
8.5%
3 6
 
7.3%
4 5
 
6.1%
9 4
 
4.9%
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 89
96.7%
Hangul 3
 
3.3%

Most frequent character per script

Common
ValueCountFrequency (%)
1 17
19.1%
2 15
16.9%
0 11
12.4%
8 9
10.1%
6 8
9.0%
7 7
7.9%
3 6
 
6.7%
4 5
 
5.6%
, 4
 
4.5%
9 4
 
4.5%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 89
96.7%
Hangul 3
 
3.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 17
19.1%
2 15
16.9%
0 11
12.4%
8 9
10.1%
6 8
9.0%
7 7
7.9%
3 6
 
6.7%
4 5
 
5.6%
, 4
 
4.5%
9 4
 
4.5%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 14
Text

MISSING 

Distinct24
Distinct (%)72.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:42:53.961272image/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

Unique20 ?
Unique (%)60.6%

Sample

1st row운암1동
2nd row7,463
3rd row19,245
4th row26
5th row17
ValueCountFrequency (%)
0 7
21.2%
17 2
 
6.1%
26 2
 
6.1%
7 2
 
6.1%
82 1
 
3.0%
19,245 1
 
3.0%
121 1
 
3.0%
7,458 1
 
3.0%
32 1
 
3.0%
5 1
 
3.0%
Other values (14) 14
42.4%
2024-02-10T09:42:54.879012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 10
13.3%
1 9
12.0%
4 9
12.0%
0 8
10.7%
7 7
9.3%
5 7
9.3%
6 6
8.0%
3 5
6.7%
, 4
 
5.3%
9 3
 
4.0%
Other values (5) 7
9.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 66
88.0%
Other Punctuation 4
 
5.3%
Other Letter 3
 
4.0%
Dash Punctuation 2
 
2.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 10
15.2%
1 9
13.6%
4 9
13.6%
0 8
12.1%
7 7
10.6%
5 7
10.6%
6 6
9.1%
3 5
7.6%
9 3
 
4.5%
8 2
 
3.0%
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 72
96.0%
Hangul 3
 
4.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 10
13.9%
1 9
12.5%
4 9
12.5%
0 8
11.1%
7 7
9.7%
5 7
9.7%
6 6
8.3%
3 5
6.9%
, 4
 
5.6%
9 3
 
4.2%
Other values (2) 4
 
5.6%
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 (%)
2 10
13.9%
1 9
12.5%
4 9
12.5%
0 8
11.1%
7 7
9.7%
5 7
9.7%
6 6
8.3%
3 5
6.9%
, 4
 
5.6%
9 3
 
4.2%
Other values (2) 4
 
5.6%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 15
Text

MISSING 

Distinct23
Distinct (%)69.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:42:55.215962image/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

Unique18 ?
Unique (%)54.5%

Sample

1st row운암2동
2nd row6,117
3rd row11,907
4th row55
5th row7
ValueCountFrequency (%)
0 7
21.2%
48 2
 
6.1%
55 2
 
6.1%
53 2
 
6.1%
1 2
 
6.1%
73 1
 
3.0%
7 1
 
3.0%
74 1
 
3.0%
11,849 1
 
3.0%
6,104 1
 
3.0%
Other values (13) 13
39.4%
2024-02-10T09:42:56.400094image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 14
18.7%
0 11
14.7%
4 10
13.3%
5 7
9.3%
7 7
9.3%
8 5
 
6.7%
3 5
 
6.7%
, 4
 
5.3%
6 3
 
4.0%
9 2
 
2.7%
Other values (5) 7
9.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 66
88.0%
Other Punctuation 4
 
5.3%
Other Letter 3
 
4.0%
Dash Punctuation 2
 
2.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 14
21.2%
0 11
16.7%
4 10
15.2%
5 7
10.6%
7 7
10.6%
8 5
 
7.6%
3 5
 
7.6%
6 3
 
4.5%
9 2
 
3.0%
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 (%)
- 2
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
1 14
19.4%
0 11
15.3%
4 10
13.9%
5 7
9.7%
7 7
9.7%
8 5
 
6.9%
3 5
 
6.9%
, 4
 
5.6%
6 3
 
4.2%
9 2
 
2.8%
Other values (2) 4
 
5.6%
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 14
19.4%
0 11
15.3%
4 10
13.9%
5 7
9.7%
7 7
9.7%
8 5
 
6.9%
3 5
 
6.9%
, 4
 
5.6%
6 3
 
4.2%
9 2
 
2.8%
Other values (2) 4
 
5.6%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 16
Text

MISSING 

Distinct23
Distinct (%)69.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:42:56.822457image/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 row운암3동
2nd row5,059
3rd row12,528
4th row29
5th row15
ValueCountFrequency (%)
0 8
24.2%
5,059 2
 
6.1%
29 2
 
6.1%
15 2
 
6.1%
59 1
 
3.0%
12,528 1
 
3.0%
41 1
 
3.0%
2 1
 
3.0%
10 1
 
3.0%
54 1
 
3.0%
Other values (13) 13
39.4%
2024-02-10T09:42:57.648265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 12
16.2%
5 11
14.9%
1 10
13.5%
9 7
9.5%
2 7
9.5%
4 6
8.1%
3 6
8.1%
, 4
 
5.4%
6 3
 
4.1%
7 2
 
2.7%
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 12
18.2%
5 11
16.7%
1 10
15.2%
9 7
10.6%
2 7
10.6%
4 6
9.1%
3 6
9.1%
6 3
 
4.5%
7 2
 
3.0%
8 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 12
16.9%
5 11
15.5%
1 10
14.1%
9 7
9.9%
2 7
9.9%
4 6
8.5%
3 6
8.5%
, 4
 
5.6%
6 3
 
4.2%
7 2
 
2.8%
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 12
16.9%
5 11
15.5%
1 10
14.1%
9 7
9.9%
2 7
9.9%
4 6
8.5%
3 6
8.5%
, 4
 
5.6%
6 3
 
4.2%
7 2
 
2.8%
Other values (2) 3
 
4.2%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 17
Text

MISSING 

Distinct26
Distinct (%)78.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:42:57.992434image/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

Unique24 ?
Unique (%)72.7%

Sample

1st row동림동
2nd row9,837
3rd row23,088
4th row55
5th row8
ValueCountFrequency (%)
0 7
21.2%
8 2
 
6.1%
119 1
 
3.0%
23,058 1
 
3.0%
9,850 1
 
3.0%
1 1
 
3.0%
30 1
 
3.0%
13 1
 
3.0%
12 1
 
3.0%
76 1
 
3.0%
Other values (16) 16
48.5%
2024-02-10T09:42:58.932762image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 13
16.7%
1 11
14.1%
8 9
11.5%
3 8
10.3%
9 8
10.3%
5 6
7.7%
2 5
 
6.4%
, 4
 
5.1%
6 4
 
5.1%
7 3
 
3.8%
Other values (4) 7
9.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 69
88.5%
Other Punctuation 4
 
5.1%
Other Letter 3
 
3.8%
Dash Punctuation 2
 
2.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 13
18.8%
1 11
15.9%
8 9
13.0%
3 8
11.6%
9 8
11.6%
5 6
8.7%
2 5
 
7.2%
6 4
 
5.8%
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 (%)
- 2
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
0 13
17.3%
1 11
14.7%
8 9
12.0%
3 8
10.7%
9 8
10.7%
5 6
8.0%
2 5
 
6.7%
, 4
 
5.3%
6 4
 
5.3%
7 3
 
4.0%
Other values (2) 4
 
5.3%
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 13
17.3%
1 11
14.7%
8 9
12.0%
3 8
10.7%
9 8
10.7%
5 6
8.0%
2 5
 
6.7%
, 4
 
5.3%
6 4
 
5.3%
7 3
 
4.0%
Other values (2) 4
 
5.3%
Hangul
ValueCountFrequency (%)
2
66.7%
1
33.3%

Unnamed: 18
Text

MISSING 

Distinct26
Distinct (%)78.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:42:59.443037image/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 row우산동
2nd row5,624
3rd row10,191
4th row60
5th row9
ValueCountFrequency (%)
0 5
 
15.2%
50 2
 
6.1%
1 2
 
6.1%
11 2
 
6.1%
3 1
 
3.0%
107 1
 
3.0%
62 1
 
3.0%
10,180 1
 
3.0%
5,613 1
 
3.0%
2 1
 
3.0%
Other values (16) 16
48.5%
2024-02-10T09:43:00.294401image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 17
23.0%
0 14
18.9%
5 7
9.5%
3 7
9.5%
6 5
 
6.8%
2 5
 
6.8%
, 4
 
5.4%
4 4
 
5.4%
- 2
 
2.7%
9 2
 
2.7%
Other values (5) 7
9.5%

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 (%)
1 17
26.2%
0 14
21.5%
5 7
10.8%
3 7
10.8%
6 5
 
7.7%
2 5
 
7.7%
4 4
 
6.2%
9 2
 
3.1%
8 2
 
3.1%
7 2
 
3.1%
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 (%)
1 17
23.9%
0 14
19.7%
5 7
9.9%
3 7
9.9%
6 5
 
7.0%
2 5
 
7.0%
, 4
 
5.6%
4 4
 
5.6%
- 2
 
2.8%
9 2
 
2.8%
Other values (2) 4
 
5.6%
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 17
23.9%
0 14
19.7%
5 7
9.9%
3 7
9.9%
6 5
 
7.0%
2 5
 
7.0%
, 4
 
5.6%
4 4
 
5.6%
- 2
 
2.8%
9 2
 
2.8%
Other values (2) 4
 
5.6%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 19
Text

MISSING 

Distinct21
Distinct (%)63.6%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:43:00.715077image/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

Unique16 ?
Unique (%)48.5%

Sample

1st row풍향동
2nd row2,759
3rd row5,674
4th row23
5th row3
ValueCountFrequency (%)
0 8
24.2%
23 3
 
9.1%
2 2
 
6.1%
3 2
 
6.1%
22 2
 
6.1%
18 1
 
3.0%
2,758 1
 
3.0%
12 1
 
3.0%
1 1
 
3.0%
15 1
 
3.0%
Other values (11) 11
33.3%
2024-02-10T09:43:01.509704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 15
22.1%
1 9
13.2%
0 8
11.8%
3 7
10.3%
5 6
 
8.8%
, 4
 
5.9%
6 4
 
5.9%
4 4
 
5.9%
7 3
 
4.4%
8 2
 
2.9%
Other values (5) 6
 
8.8%

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 (%)
2 15
25.4%
1 9
15.3%
0 8
13.6%
3 7
11.9%
5 6
 
10.2%
6 4
 
6.8%
4 4
 
6.8%
7 3
 
5.1%
8 2
 
3.4%
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 (%)
- 2
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
2 15
23.1%
1 9
13.8%
0 8
12.3%
3 7
10.8%
5 6
 
9.2%
, 4
 
6.2%
6 4
 
6.2%
4 4
 
6.2%
7 3
 
4.6%
8 2
 
3.1%
Other values (2) 3
 
4.6%
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 (%)
2 15
23.1%
1 9
13.8%
0 8
12.3%
3 7
10.8%
5 6
 
9.2%
, 4
 
6.2%
6 4
 
6.2%
4 4
 
6.2%
7 3
 
4.6%
8 2
 
3.1%
Other values (2) 3
 
4.6%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 20
Text

MISSING 

Distinct23
Distinct (%)69.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:43:01.878417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.2727273
Min length1

Characters and Unicode

Total characters75
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

Unique19 ?
Unique (%)57.6%

Sample

1st row문화동
2nd row9,699
3rd row20,712
4th row56
5th row7
ValueCountFrequency (%)
0 8
24.2%
7 2
 
6.1%
50 2
 
6.1%
18 2
 
6.1%
56 2
 
6.1%
89 1
 
3.0%
108 1
 
3.0%
9,694 1
 
3.0%
5 1
 
3.0%
12 1
 
3.0%
Other values (12) 12
36.4%
2024-02-10T09:43:02.935807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 16
21.3%
9 10
13.3%
6 8
10.7%
8 8
10.7%
1 6
 
8.0%
2 6
 
8.0%
5 5
 
6.7%
, 4
 
5.3%
4 4
 
5.3%
7 3
 
4.0%
Other values (4) 5
 
6.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 66
88.0%
Other Punctuation 4
 
5.3%
Other Letter 3
 
4.0%
Dash Punctuation 2
 
2.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 16
24.2%
9 10
15.2%
6 8
12.1%
8 8
12.1%
1 6
 
9.1%
2 6
 
9.1%
5 5
 
7.6%
4 4
 
6.1%
7 3
 
4.5%
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 72
96.0%
Hangul 3
 
4.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 16
22.2%
9 10
13.9%
6 8
11.1%
8 8
11.1%
1 6
 
8.3%
2 6
 
8.3%
5 5
 
6.9%
, 4
 
5.6%
4 4
 
5.6%
7 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 (%)
0 16
22.2%
9 10
13.9%
6 8
11.1%
8 8
11.1%
1 6
 
8.3%
2 6
 
8.3%
5 5
 
6.9%
, 4
 
5.6%
4 4
 
5.6%
7 3
 
4.2%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 21
Text

MISSING 

Distinct25
Distinct (%)75.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:43:03.300416image/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

Unique22 ?
Unique (%)66.7%

Sample

1st row문흥1동
2nd row6,478
3rd row15,766
4th row29
5th row9
ValueCountFrequency (%)
0 7
21.2%
9 2
 
6.1%
29 2
 
6.1%
6 1
 
3.0%
158 1
 
3.0%
6,475 1
 
3.0%
57 1
 
3.0%
3 1
 
3.0%
8 1
 
3.0%
52 1
 
3.0%
Other values (15) 15
45.5%
2024-02-10T09:43:04.019254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 11
15.1%
6 8
11.0%
5 8
11.0%
1 7
9.6%
4 7
9.6%
7 7
9.6%
2 5
6.8%
9 5
6.8%
8 5
6.8%
, 4
 
5.5%
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 (%)
0 11
17.2%
6 8
12.5%
5 8
12.5%
1 7
10.9%
4 7
10.9%
7 7
10.9%
2 5
7.8%
9 5
7.8%
8 5
7.8%
3 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 (%)
0 11
15.7%
6 8
11.4%
5 8
11.4%
1 7
10.0%
4 7
10.0%
7 7
10.0%
2 5
7.1%
9 5
7.1%
8 5
7.1%
, 4
 
5.7%
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 (%)
0 11
15.7%
6 8
11.4%
5 8
11.4%
1 7
10.0%
4 7
10.0%
7 7
10.0%
2 5
7.1%
9 5
7.1%
8 5
7.1%
, 4
 
5.7%
Other values (2) 3
 
4.3%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 22
Text

MISSING 

Distinct25
Distinct (%)75.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:43:04.529287image/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

Unique22 ?
Unique (%)66.7%

Sample

1st row문흥2동
2nd row7,388
3rd row15,553
4th row32
5th row4
ValueCountFrequency (%)
0 7
21.2%
4 2
 
6.1%
32 2
 
6.1%
7 1
 
3.0%
64 1
 
3.0%
7,382 1
 
3.0%
18 1
 
3.0%
6 1
 
3.0%
1 1
 
3.0%
5 1
 
3.0%
Other values (15) 15
45.5%
2024-02-10T09:43:05.425257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 13
17.8%
0 9
12.3%
3 8
11.0%
1 7
9.6%
6 6
8.2%
2 5
 
6.8%
4 5
 
6.8%
7 5
 
6.8%
8 5
 
6.8%
, 4
 
5.5%
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 (%)
5 13
20.3%
0 9
14.1%
3 8
12.5%
1 7
10.9%
6 6
9.4%
2 5
 
7.8%
4 5
 
7.8%
7 5
 
7.8%
8 5
 
7.8%
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 (%)
5 13
18.6%
0 9
12.9%
3 8
11.4%
1 7
10.0%
6 6
8.6%
2 5
 
7.1%
4 5
 
7.1%
7 5
 
7.1%
8 5
 
7.1%
, 4
 
5.7%
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 (%)
5 13
18.6%
0 9
12.9%
3 8
11.4%
1 7
10.0%
6 6
8.6%
2 5
 
7.1%
4 5
 
7.1%
7 5
 
7.1%
8 5
 
7.1%
, 4
 
5.7%
Other values (2) 3
 
4.3%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 23
Text

MISSING 

Distinct24
Distinct (%)72.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:43:05.793398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length2.0909091
Min length1

Characters and Unicode

Total characters69
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 row두암1동
2nd row4,010
3rd row7,712
4th row22
5th row7
ValueCountFrequency (%)
0 6
18.2%
1 4
 
12.1%
7 2
 
6.1%
20 2
 
6.1%
42 1
 
3.0%
22 1
 
3.0%
46 1
 
3.0%
7,692 1
 
3.0%
4,011 1
 
3.0%
2 1
 
3.0%
Other values (13) 13
39.4%
2024-02-10T09:43:06.732292image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 14
20.3%
0 13
18.8%
2 11
15.9%
4 7
10.1%
7 6
8.7%
, 4
 
5.8%
3 3
 
4.3%
8 2
 
2.9%
5 2
 
2.9%
6 2
 
2.9%
Other values (5) 5
 
7.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 61
88.4%
Other Punctuation 4
 
5.8%
Other Letter 3
 
4.3%
Dash Punctuation 1
 
1.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 14
23.0%
0 13
21.3%
2 11
18.0%
4 7
11.5%
7 6
9.8%
3 3
 
4.9%
8 2
 
3.3%
5 2
 
3.3%
6 2
 
3.3%
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 (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 66
95.7%
Hangul 3
 
4.3%

Most frequent character per script

Common
ValueCountFrequency (%)
1 14
21.2%
0 13
19.7%
2 11
16.7%
4 7
10.6%
7 6
9.1%
, 4
 
6.1%
3 3
 
4.5%
8 2
 
3.0%
5 2
 
3.0%
6 2
 
3.0%
Other values (2) 2
 
3.0%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 66
95.7%
Hangul 3
 
4.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 14
21.2%
0 13
19.7%
2 11
16.7%
4 7
10.6%
7 6
9.1%
, 4
 
6.1%
3 3
 
4.5%
8 2
 
3.0%
5 2
 
3.0%
6 2
 
3.0%
Other values (2) 2
 
3.0%
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
2024-02-10T09:43:07.177296image/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

Unique18 ?
Unique (%)54.5%

Sample

1st row두암2동
2nd row7,698
3rd row15,929
4th row56
5th row9
ValueCountFrequency (%)
0 8
24.2%
9 3
 
9.1%
56 2
 
6.1%
46 2
 
6.1%
44 1
 
3.0%
177 1
 
3.0%
7,691 1
 
3.0%
36 1
 
3.0%
7 1
 
3.0%
67 1
 
3.0%
Other values (12) 12
36.4%
2024-02-10T09:43:07.929322image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6 13
17.8%
9 9
12.3%
0 8
11.0%
4 8
11.0%
7 7
9.6%
1 6
8.2%
5 5
 
6.8%
, 4
 
5.5%
8 4
 
5.5%
2 2
 
2.7%
Other values (5) 7
9.6%

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 (%)
6 13
20.3%
9 9
14.1%
0 8
12.5%
4 8
12.5%
7 7
10.9%
1 6
9.4%
5 5
 
7.8%
8 4
 
6.2%
2 2
 
3.1%
3 2
 
3.1%
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 (%)
6 13
18.6%
9 9
12.9%
0 8
11.4%
4 8
11.4%
7 7
10.0%
1 6
8.6%
5 5
 
7.1%
, 4
 
5.7%
8 4
 
5.7%
2 2
 
2.9%
Other values (2) 4
 
5.7%
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 (%)
6 13
18.6%
9 9
12.9%
0 8
11.4%
4 8
11.4%
7 7
10.0%
1 6
8.6%
5 5
 
7.1%
, 4
 
5.7%
8 4
 
5.7%
2 2
 
2.9%
Other values (2) 4
 
5.7%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 25
Text

MISSING 

Distinct25
Distinct (%)75.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:43:08.335662image/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 row두암3동
2nd row7,766
3rd row13,203
4th row47
5th row8
ValueCountFrequency (%)
0 7
21.2%
8 2
 
6.1%
1 2
 
6.1%
47 2
 
6.1%
70 1
 
3.0%
66 1
 
3.0%
13,171 1
 
3.0%
7,769 1
 
3.0%
32 1
 
3.0%
3 1
 
3.0%
Other values (14) 14
42.4%
2024-02-10T09:43:09.150138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 11
14.9%
0 10
13.5%
1 10
13.5%
7 9
12.2%
6 8
10.8%
8 5
6.8%
4 4
 
5.4%
, 4
 
5.4%
2 4
 
5.4%
5 2
 
2.7%
Other values (5) 7
9.5%

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 (%)
3 11
16.9%
0 10
15.4%
1 10
15.4%
7 9
13.8%
6 8
12.3%
8 5
7.7%
4 4
 
6.2%
2 4
 
6.2%
5 2
 
3.1%
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 (%)
- 2
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
3 11
15.5%
0 10
14.1%
1 10
14.1%
7 9
12.7%
6 8
11.3%
8 5
7.0%
4 4
 
5.6%
, 4
 
5.6%
2 4
 
5.6%
5 2
 
2.8%
Other values (2) 4
 
5.6%
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 (%)
3 11
15.5%
0 10
14.1%
1 10
14.1%
7 9
12.7%
6 8
11.3%
8 5
7.0%
4 4
 
5.6%
, 4
 
5.6%
2 4
 
5.6%
5 2
 
2.8%
Other values (2) 4
 
5.6%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 26
Text

MISSING 

Distinct21
Distinct (%)63.6%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:43:09.561888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.2121212
Min length1

Characters and Unicode

Total characters73
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

Unique15 ?
Unique (%)45.5%

Sample

1st row삼각동
2nd row6,038
3rd row13,881
4th row31
5th row4
ValueCountFrequency (%)
0 8
24.2%
4 2
 
6.1%
65 2
 
6.1%
56 2
 
6.1%
26 2
 
6.1%
31 2
 
6.1%
11 1
 
3.0%
127 1
 
3.0%
6,052 1
 
3.0%
10 1
 
3.0%
Other values (11) 11
33.3%
2024-02-10T09:43:10.534198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 14
19.2%
0 11
15.1%
6 9
12.3%
5 7
9.6%
4 6
8.2%
2 6
8.2%
3 5
 
6.8%
, 4
 
5.5%
8 4
 
5.5%
7 3
 
4.1%
Other values (4) 4
 
5.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 65
89.0%
Other Punctuation 4
 
5.5%
Other Letter 3
 
4.1%
Dash Punctuation 1
 
1.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 14
21.5%
0 11
16.9%
6 9
13.8%
5 7
10.8%
4 6
9.2%
2 6
9.2%
3 5
 
7.7%
8 4
 
6.2%
7 3
 
4.6%
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 70
95.9%
Hangul 3
 
4.1%

Most frequent character per script

Common
ValueCountFrequency (%)
1 14
20.0%
0 11
15.7%
6 9
12.9%
5 7
10.0%
4 6
8.6%
2 6
8.6%
3 5
 
7.1%
, 4
 
5.7%
8 4
 
5.7%
7 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 (%)
1 14
20.0%
0 11
15.7%
6 9
12.9%
5 7
10.0%
4 6
8.6%
2 6
8.6%
3 5
 
7.1%
, 4
 
5.7%
8 4
 
5.7%
7 3
 
4.3%
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
2024-02-10T09:43:10.946611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length3
Mean length2.3333333
Min length1

Characters and Unicode

Total characters77
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 row11,542
3rd row29,549
4th row32
5th row11
ValueCountFrequency (%)
0 7
21.2%
11 2
 
6.1%
110 1
 
3.0%
29,495 1
 
3.0%
11,549 1
 
3.0%
1 1
 
3.0%
54 1
 
3.0%
7 1
 
3.0%
9 1
 
3.0%
91 1
 
3.0%
Other values (16) 16
48.5%
2024-02-10T09:43:11.971101image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 15
19.5%
0 10
13.0%
5 9
11.7%
3 8
10.4%
9 8
10.4%
2 7
9.1%
4 5
 
6.5%
, 4
 
5.2%
7 4
 
5.2%
8 2
 
2.6%
Other values (5) 5
 
6.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 69
89.6%
Other Punctuation 4
 
5.2%
Other Letter 3
 
3.9%
Dash Punctuation 1
 
1.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 15
21.7%
0 10
14.5%
5 9
13.0%
3 8
11.6%
9 8
11.6%
2 7
10.1%
4 5
 
7.2%
7 4
 
5.8%
8 2
 
2.9%
6 1
 
1.4%
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 74
96.1%
Hangul 3
 
3.9%

Most frequent character per script

Common
ValueCountFrequency (%)
1 15
20.3%
0 10
13.5%
5 9
12.2%
3 8
10.8%
9 8
10.8%
2 7
9.5%
4 5
 
6.8%
, 4
 
5.4%
7 4
 
5.4%
8 2
 
2.7%
Other values (2) 2
 
2.7%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 74
96.1%
Hangul 3
 
3.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 15
20.3%
0 10
13.5%
5 9
12.2%
3 8
10.8%
9 8
10.8%
2 7
9.5%
4 5
 
6.8%
, 4
 
5.4%
7 4
 
5.4%
8 2
 
2.7%
Other values (2) 2
 
2.7%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 28
Text

MISSING 

Distinct26
Distinct (%)78.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:43:12.375548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.1212121
Min length1

Characters and Unicode

Total characters70
Distinct characters13
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

Unique23 ?
Unique (%)69.7%

Sample

1st row매곡동
2nd row5,502
3rd row13,726
4th row20
5th row5
ValueCountFrequency (%)
0 6
 
18.2%
30 2
 
6.1%
5 2
 
6.1%
47 1
 
3.0%
93 1
 
3.0%
13,756 1
 
3.0%
5,516 1
 
3.0%
4 1
 
3.0%
14 1
 
3.0%
3 1
 
3.0%
Other values (16) 16
48.5%
2024-02-10T09:43:13.438795image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 12
17.1%
5 9
12.9%
3 8
11.4%
6 7
10.0%
1 7
10.0%
4 7
10.0%
2 6
8.6%
, 4
 
5.7%
9 4
 
5.7%
7 3
 
4.3%
Other values (3) 3
 
4.3%

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 (%)
0 12
19.0%
5 9
14.3%
3 8
12.7%
6 7
11.1%
1 7
11.1%
4 7
11.1%
2 6
9.5%
9 4
 
6.3%
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 (%)
0 12
17.9%
5 9
13.4%
3 8
11.9%
6 7
10.4%
1 7
10.4%
4 7
10.4%
2 6
9.0%
, 4
 
6.0%
9 4
 
6.0%
7 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 (%)
0 12
17.9%
5 9
13.4%
3 8
11.9%
6 7
10.4%
1 7
10.4%
4 7
10.4%
2 6
9.0%
, 4
 
6.0%
9 4
 
6.0%
7 3
 
4.5%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 29
Text

MISSING 

Distinct26
Distinct (%)78.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:43:13.930584image/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 row5,506
3rd row10,807
4th row50
5th row8
ValueCountFrequency (%)
0 7
21.2%
8 2
 
6.1%
70 1
 
3.0%
10,767 1
 
3.0%
5,510 1
 
3.0%
1 1
 
3.0%
40 1
 
3.0%
4 1
 
3.0%
9 1
 
3.0%
36 1
 
3.0%
Other values (16) 16
48.5%
2024-02-10T09:43:14.840590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 17
23.3%
1 9
12.3%
5 7
9.6%
7 7
9.6%
4 6
 
8.2%
3 6
 
8.2%
8 4
 
5.5%
, 4
 
5.5%
6 4
 
5.5%
2 2
 
2.7%
Other values (5) 7
9.6%

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 (%)
0 17
26.6%
1 9
14.1%
5 7
10.9%
7 7
10.9%
4 6
 
9.4%
3 6
 
9.4%
8 4
 
6.2%
6 4
 
6.2%
2 2
 
3.1%
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 (%)
- 2
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
0 17
24.3%
1 9
12.9%
5 7
10.0%
7 7
10.0%
4 6
 
8.6%
3 6
 
8.6%
8 4
 
5.7%
, 4
 
5.7%
6 4
 
5.7%
2 2
 
2.9%
Other values (2) 4
 
5.7%
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 (%)
0 17
24.3%
1 9
12.9%
5 7
10.0%
7 7
10.0%
4 6
 
8.6%
3 6
 
8.6%
8 4
 
5.7%
, 4
 
5.7%
6 4
 
5.7%
2 2
 
2.9%
Other values (2) 4
 
5.7%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 30
Text

MISSING 

Distinct26
Distinct (%)78.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:43:15.300026image/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 row오치2동
2nd row6,991
3rd row12,386
4th row34
5th row8
ValueCountFrequency (%)
0 6
 
18.2%
2 3
 
9.1%
12,386 1
 
3.0%
34 1
 
3.0%
36 1
 
3.0%
12,351 1
 
3.0%
6,993 1
 
3.0%
35 1
 
3.0%
14 1
 
3.0%
54 1
 
3.0%
Other values (16) 16
48.5%
2024-02-10T09:43:16.505723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 10
13.7%
1 9
12.3%
5 8
11.0%
3 8
11.0%
2 7
9.6%
6 6
8.2%
9 6
8.2%
8 5
6.8%
, 4
 
5.5%
4 4
 
5.5%
Other values (5) 6
8.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 65
89.0%
Other Punctuation 4
 
5.5%
Other Letter 3
 
4.1%
Dash Punctuation 1
 
1.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 10
15.4%
1 9
13.8%
5 8
12.3%
3 8
12.3%
2 7
10.8%
6 6
9.2%
9 6
9.2%
8 5
7.7%
4 4
 
6.2%
7 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 70
95.9%
Hangul 3
 
4.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 10
14.3%
1 9
12.9%
5 8
11.4%
3 8
11.4%
2 7
10.0%
6 6
8.6%
9 6
8.6%
8 5
7.1%
, 4
 
5.7%
4 4
 
5.7%
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 (%)
0 10
14.3%
1 9
12.9%
5 8
11.4%
3 8
11.4%
2 7
10.0%
6 6
8.6%
9 6
8.6%
8 5
7.1%
, 4
 
5.7%
4 4
 
5.7%
Other values (2) 3
 
4.3%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 31
Text

MISSING 

Distinct17
Distinct (%)51.5%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:43:17.014503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length1
Mean length1.8787879
Min length1

Characters and Unicode

Total characters62
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

Unique11 ?
Unique (%)33.3%

Sample

1st row석곡동
2nd row1,382
3rd row2,501
4th row21
5th row3
ValueCountFrequency (%)
0 7
21.2%
4 4
12.1%
21 3
9.1%
11 3
9.1%
10 3
9.1%
3 2
 
6.1%
2 2
 
6.1%
7 1
 
3.0%
1,382 1
 
3.0%
2,501 1
 
3.0%
Other values (6) 6
18.2%
2024-02-10T09:43:18.006450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 16
25.8%
0 11
17.7%
2 10
16.1%
4 5
 
8.1%
3 4
 
6.5%
, 4
 
6.5%
8 2
 
3.2%
6 2
 
3.2%
9 2
 
3.2%
7 1
 
1.6%
Other values (5) 5
 
8.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 54
87.1%
Other Punctuation 4
 
6.5%
Other Letter 3
 
4.8%
Dash Punctuation 1
 
1.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 16
29.6%
0 11
20.4%
2 10
18.5%
4 5
 
9.3%
3 4
 
7.4%
8 2
 
3.7%
6 2
 
3.7%
9 2
 
3.7%
7 1
 
1.9%
5 1
 
1.9%
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 59
95.2%
Hangul 3
 
4.8%

Most frequent character per script

Common
ValueCountFrequency (%)
1 16
27.1%
0 11
18.6%
2 10
16.9%
4 5
 
8.5%
3 4
 
6.8%
, 4
 
6.8%
8 2
 
3.4%
6 2
 
3.4%
9 2
 
3.4%
7 1
 
1.7%
Other values (2) 2
 
3.4%
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 (%)
1 16
27.1%
0 11
18.6%
2 10
16.9%
4 5
 
8.5%
3 4
 
6.8%
, 4
 
6.8%
8 2
 
3.4%
6 2
 
3.4%
9 2
 
3.4%
7 1
 
1.7%
Other values (2) 2
 
3.4%
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
2024-02-10T09:43:18.456391image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.4242424
Min length1

Characters and Unicode

Total characters80
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 row9,187
3rd row22,131
4th row62
5th row12
ValueCountFrequency (%)
0 7
21.2%
12 2
 
6.1%
62 2
 
6.1%
15 1
 
3.0%
237 1
 
3.0%
9,165 1
 
3.0%
71 1
 
3.0%
22 1
 
3.0%
11 1
 
3.0%
70 1
 
3.0%
Other values (15) 15
45.5%
2024-02-10T09:43:19.403568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 15
18.8%
1 15
18.8%
0 13
16.2%
6 7
8.8%
7 5
 
6.2%
, 4
 
5.0%
3 4
 
5.0%
4 4
 
5.0%
9 3
 
3.8%
8 3
 
3.8%
Other values (5) 7
8.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 71
88.8%
Other Punctuation 4
 
5.0%
Other Letter 3
 
3.8%
Dash Punctuation 2
 
2.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 15
21.1%
1 15
21.1%
0 13
18.3%
6 7
9.9%
7 5
 
7.0%
3 4
 
5.6%
4 4
 
5.6%
9 3
 
4.2%
8 3
 
4.2%
5 2
 
2.8%
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 77
96.2%
Hangul 3
 
3.8%

Most frequent character per script

Common
ValueCountFrequency (%)
2 15
19.5%
1 15
19.5%
0 13
16.9%
6 7
9.1%
7 5
 
6.5%
, 4
 
5.2%
3 4
 
5.2%
4 4
 
5.2%
9 3
 
3.9%
8 3
 
3.9%
Other values (2) 4
 
5.2%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 77
96.2%
Hangul 3
 
3.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 15
19.5%
1 15
19.5%
0 13
16.9%
6 7
9.1%
7 5
 
6.5%
, 4
 
5.2%
3 4
 
5.2%
4 4
 
5.2%
9 3
 
3.9%
8 3
 
3.9%
Other values (2) 4
 
5.2%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 33
Text

MISSING 

Distinct25
Distinct (%)75.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:43:19.836656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length3
Mean length2.6363636
Min length1

Characters and Unicode

Total characters87
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 row양산동
2nd row16,419
3rd row37,648
4th row63
5th row19
ValueCountFrequency (%)
0 6
 
18.2%
19 3
 
9.1%
63 2
 
6.1%
1 1
 
3.0%
212 1
 
3.0%
16,413 1
 
3.0%
97 1
 
3.0%
6 1
 
3.0%
2 1
 
3.0%
22 1
 
3.0%
Other values (15) 15
45.5%
2024-02-10T09:43:20.700937image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 20
23.0%
0 9
10.3%
9 9
10.3%
3 9
10.3%
6 7
 
8.0%
4 7
 
8.0%
2 7
 
8.0%
, 4
 
4.6%
7 4
 
4.6%
5 4
 
4.6%
Other values (5) 7
 
8.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 78
89.7%
Other Punctuation 4
 
4.6%
Other Letter 3
 
3.4%
Dash Punctuation 2
 
2.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 20
25.6%
0 9
11.5%
9 9
11.5%
3 9
11.5%
6 7
 
9.0%
4 7
 
9.0%
2 7
 
9.0%
7 4
 
5.1%
5 4
 
5.1%
8 2
 
2.6%
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 84
96.6%
Hangul 3
 
3.4%

Most frequent character per script

Common
ValueCountFrequency (%)
1 20
23.8%
0 9
10.7%
9 9
10.7%
3 9
10.7%
6 7
 
8.3%
4 7
 
8.3%
2 7
 
8.3%
, 4
 
4.8%
7 4
 
4.8%
5 4
 
4.8%
Other values (2) 4
 
4.8%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 84
96.6%
Hangul 3
 
3.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 20
23.8%
0 9
10.7%
9 9
10.7%
3 9
10.7%
6 7
 
8.3%
4 7
 
8.3%
2 7
 
8.3%
, 4
 
4.8%
7 4
 
4.8%
5 4
 
4.8%
Other values (2) 4
 
4.8%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 34
Text

MISSING 

Distinct26
Distinct (%)78.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:43:21.097138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length3
Mean length2.4545455
Min length1

Characters and Unicode

Total characters81
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 row신용동
2nd row11,833
3rd row29,677
4th row7
5th row10
ValueCountFrequency (%)
0 7
21.2%
81 2
 
6.1%
10 2
 
6.1%
161 1
 
3.0%
149 1
 
3.0%
29,596 1
 
3.0%
11,818 1
 
3.0%
2 1
 
3.0%
15 1
 
3.0%
6 1
 
3.0%
Other values (15) 15
45.5%
2024-02-10T09:43:21.987004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 21
25.9%
0 11
13.6%
6 9
11.1%
9 8
 
9.9%
8 7
 
8.6%
3 5
 
6.2%
, 4
 
4.9%
2 4
 
4.9%
7 3
 
3.7%
4 2
 
2.5%
Other values (5) 7
 
8.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 72
88.9%
Other Punctuation 4
 
4.9%
Other Letter 3
 
3.7%
Dash Punctuation 2
 
2.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 21
29.2%
0 11
15.3%
6 9
12.5%
9 8
 
11.1%
8 7
 
9.7%
3 5
 
6.9%
2 4
 
5.6%
7 3
 
4.2%
4 2
 
2.8%
5 2
 
2.8%
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 78
96.3%
Hangul 3
 
3.7%

Most frequent character per script

Common
ValueCountFrequency (%)
1 21
26.9%
0 11
14.1%
6 9
11.5%
9 8
 
10.3%
8 7
 
9.0%
3 5
 
6.4%
, 4
 
5.1%
2 4
 
5.1%
7 3
 
3.8%
4 2
 
2.6%
Other values (2) 4
 
5.1%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 78
96.3%
Hangul 3
 
3.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 21
26.9%
0 11
14.1%
6 9
11.5%
9 8
 
10.3%
8 7
 
9.0%
3 5
 
6.4%
, 4
 
5.1%
2 4
 
5.1%
7 3
 
3.8%
4 2
 
2.6%
Other values (2) 4
 
5.1%
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>2022.06.13<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>2022.05 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>196,9953,0064,3403,3702,3374,5487,209<NA>17,8877,4636,1175,0599,8375,6242,7599,6996,4787,3884,0107,6987,7666,03811,5425,5025,5066,9911,3829,18716,41911,833
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5<NA>전월말거주불명자수<NA><NA><NA>1,268576342513884<NA>12326552955602356293222564731322050342162637
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7<NA>증 가 요 인전 입<NA>4,1295525125420083184<NA>32412110191199103431801021318114412012117511910812621160313219
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34<NA>금월말재외국민등록자수<NA><NA><NA>222063452<NA>20178158727947984115893121910

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