Overview

Dataset statistics

Number of variables20
Number of observations35
Missing cells193
Missing cells (%)27.6%
Duplicate rows1
Duplicate rows (%)2.9%
Total size in memory5.6 KiB
Average record size in memory164.8 B

Variable types

Unsupported1
Text18
DateTime1

Dataset

Description2023-02-23
Author주민등록인구통계
URLhttps://bigdata.gwangju.go.kr/usr/dataSet/getDataDetailView.rd?dataSetUncd=DS000201926

Alerts

Unnamed: 12 has constant value ""Constant
Dataset has 1 (2.9%) 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: 0 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-02-10 10:08:10.528165
Analysis finished2024-02-10 10:08:17.096904
Duration6.57 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
2024-02-10T10:08:17.399409image/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%
2024-02-10T10:08:18.567614image/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
2024-02-10T10:08:19.166699image/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%
2024-02-10T10:08:20.515977image/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
2024-02-10T10:08:21.019192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length9
Mean length3.4166667
Min length1

Characters and Unicode

Total characters41
Distinct characters21
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 동구
2nd row2023.01 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%
동구 1
7.1%
2023.01 1
7.1%
현재 1
7.1%
2024-02-10T10:08:22.260613image/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
 
4.9%
2
 
4.9%
2
 
4.9%
2
 
4.9%
2
 
4.9%
2
 
4.9%
Other values (11) 13
31.7%

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 2
33.3%
0 2
33.3%
3 1
16.7%
1 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 2
20.0%
0 2
20.0%
3 1
 
10.0%
1 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 2
20.0%
0 2
20.0%
3 1
 
10.0%
1 1
 
10.0%
. 1
 
10.0%

Unnamed: 4
Text

MISSING 

Distinct2
Distinct (%)50.0%
Missing31
Missing (%)88.6%
Memory size412.0 B
2024-02-10T10:08:22.601960image/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%
2024-02-10T10:08:23.397747image/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 

Distinct27
Distinct (%)81.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T10:08:23.718885image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length3.0606061
Min length1

Characters and Unicode

Total characters101
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

Unique24 ?
Unique (%)72.7%

Sample

1st row합 계
2nd row54,072
3rd row105,909
4th row738
5th row103
ValueCountFrequency (%)
0 5
 
14.7%
2 2
 
5.9%
22 2
 
5.9%
258 2
 
5.9%
575 1
 
2.9%
738 1
 
2.9%
103 1
 
2.9%
725 1
 
2.9%
105,887 1
 
2.9%
54,094 1
 
2.9%
Other values (17) 17
50.0%
2024-02-10T10:08:24.685188image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 15
14.9%
0 14
13.9%
2 11
10.9%
3 9
8.9%
8 8
7.9%
7 8
7.9%
1 8
7.9%
6 7
6.9%
, 6
 
5.9%
9 5
 
5.0%
Other values (5) 10
9.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 89
88.1%
Other Punctuation 6
 
5.9%
Space Separator 2
 
2.0%
Dash Punctuation 2
 
2.0%
Other Letter 2
 
2.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 15
16.9%
0 14
15.7%
2 11
12.4%
3 9
10.1%
8 8
9.0%
7 8
9.0%
1 8
9.0%
6 7
7.9%
9 5
 
5.6%
4 4
 
4.5%
Other Letter
ValueCountFrequency (%)
1
50.0%
1
50.0%
Other Punctuation
ValueCountFrequency (%)
, 6
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 99
98.0%
Hangul 2
 
2.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 15
15.2%
0 14
14.1%
2 11
11.1%
3 9
9.1%
8 8
8.1%
7 8
8.1%
1 8
8.1%
6 7
7.1%
, 6
 
6.1%
9 5
 
5.1%
Other values (3) 8
8.1%
Hangul
ValueCountFrequency (%)
1
50.0%
1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 99
98.0%
Hangul 2
 
2.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 15
15.2%
0 14
14.1%
2 11
11.1%
3 9
9.1%
8 8
8.1%
7 8
8.1%
1 8
8.1%
6 7
7.1%
, 6
 
6.1%
9 5
 
5.1%
Other values (3) 8
8.1%
Hangul
ValueCountFrequency (%)
1
50.0%
1
50.0%

Unnamed: 6
Text

MISSING 

Distinct24
Distinct (%)72.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T10:08:25.034281image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
Mean length2.030303
Min length1

Characters and Unicode

Total characters67
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

Unique20 ?
Unique (%)60.6%

Sample

1st row충장동
2nd row3,965
3rd row5,077
4th row36
5th row7
ValueCountFrequency (%)
0 7
21.2%
38 2
 
6.1%
7 2
 
6.1%
3 2
 
6.1%
47 1
 
3.0%
36 1
 
3.0%
165 1
 
3.0%
5,157 1
 
3.0%
4,036 1
 
3.0%
80 1
 
3.0%
Other values (14) 14
42.4%
2024-02-10T10:08:25.946110image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 10
14.9%
3 10
14.9%
7 10
14.9%
6 7
10.4%
8 5
7.5%
5 5
7.5%
4 4
 
6.0%
1 4
 
6.0%
, 4
 
6.0%
9 3
 
4.5%
Other values (4) 5
7.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 60
89.6%
Other Punctuation 4
 
6.0%
Other Letter 3
 
4.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 10
16.7%
3 10
16.7%
7 10
16.7%
6 7
11.7%
8 5
8.3%
5 5
8.3%
4 4
 
6.7%
1 4
 
6.7%
9 3
 
5.0%
2 2
 
3.3%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 64
95.5%
Hangul 3
 
4.5%

Most frequent character per script

Common
ValueCountFrequency (%)
0 10
15.6%
3 10
15.6%
7 10
15.6%
6 7
10.9%
8 5
7.8%
5 5
7.8%
4 4
 
6.2%
1 4
 
6.2%
, 4
 
6.2%
9 3
 
4.7%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 64
95.5%
Hangul 3
 
4.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 10
15.6%
3 10
15.6%
7 10
15.6%
6 7
10.9%
8 5
7.8%
5 5
7.8%
4 4
 
6.2%
1 4
 
6.2%
, 4
 
6.2%
9 3
 
4.7%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 7
Text

MISSING 

Distinct24
Distinct (%)72.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T10:08:26.333018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
Mean length2.1212121
Min length1

Characters and Unicode

Total characters70
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 row동명동
2nd row2,426
3rd row3,743
4th row118
5th row7
ValueCountFrequency (%)
0 8
24.2%
7 3
 
9.1%
40 2
 
6.1%
33 1
 
3.0%
118 1
 
3.0%
22 1
 
3.0%
3,725 1
 
3.0%
2,419 1
 
3.0%
1 1
 
3.0%
18 1
 
3.0%
Other values (13) 13
39.4%
2024-02-10T10:08:27.361548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 10
14.3%
7 9
12.9%
3 9
12.9%
4 7
10.0%
2 7
10.0%
1 7
10.0%
9 4
 
5.7%
, 4
 
5.7%
6 3
 
4.3%
8 3
 
4.3%
Other values (4) 7
10.0%

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 10
16.7%
7 9
15.0%
3 9
15.0%
4 7
11.7%
2 7
11.7%
1 7
11.7%
9 4
 
6.7%
6 3
 
5.0%
8 3
 
5.0%
5 1
 
1.7%
Other Letter
ValueCountFrequency (%)
2
66.7%
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 10
14.9%
7 9
13.4%
3 9
13.4%
4 7
10.4%
2 7
10.4%
1 7
10.4%
9 4
 
6.0%
, 4
 
6.0%
6 3
 
4.5%
8 3
 
4.5%
Other values (2) 4
 
6.0%
Hangul
ValueCountFrequency (%)
2
66.7%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 10
14.9%
7 9
13.4%
3 9
13.4%
4 7
10.4%
2 7
10.4%
1 7
10.4%
9 4
 
6.0%
, 4
 
6.0%
6 3
 
4.5%
8 3
 
4.5%
Other values (2) 4
 
6.0%
Hangul
ValueCountFrequency (%)
2
66.7%
1
33.3%

Unnamed: 8
Text

MISSING 

Distinct23
Distinct (%)69.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T10:08:27.682720image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.2121212
Min length1

Characters and Unicode

Total characters73
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

Unique19 ?
Unique (%)57.6%

Sample

1st row계림1동
2nd row5,795
3rd row10,507
4th row79
5th row12
ValueCountFrequency (%)
0 8
24.2%
12 2
 
6.1%
79 2
 
6.1%
80 2
 
6.1%
21 1
 
3.0%
10,507 1
 
3.0%
70 1
 
3.0%
5,802 1
 
3.0%
17 1
 
3.0%
7 1
 
3.0%
Other values (13) 13
39.4%
2024-02-10T10:08:28.557830image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 15
20.5%
1 11
15.1%
7 10
13.7%
6 7
9.6%
8 5
 
6.8%
2 5
 
6.8%
5 5
 
6.8%
9 4
 
5.5%
4 4
 
5.5%
, 4
 
5.5%
Other values (3) 3
 
4.1%

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 (%)
0 15
22.7%
1 11
16.7%
7 10
15.2%
6 7
10.6%
8 5
 
7.6%
2 5
 
7.6%
5 5
 
7.6%
9 4
 
6.1%
4 4
 
6.1%
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 (%)
0 15
21.4%
1 11
15.7%
7 10
14.3%
6 7
10.0%
8 5
 
7.1%
2 5
 
7.1%
5 5
 
7.1%
9 4
 
5.7%
4 4
 
5.7%
, 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 15
21.4%
1 11
15.7%
7 10
14.3%
6 7
10.0%
8 5
 
7.1%
2 5
 
7.1%
5 5
 
7.1%
9 4
 
5.7%
4 4
 
5.7%
, 4
 
5.7%
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
2024-02-10T10:08:28.892356image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.3030303
Min length1

Characters and Unicode

Total characters76
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

Unique20 ?
Unique (%)60.6%

Sample

1st row계림2동
2nd row5,420
3rd row12,893
4th row28
5th row12
ValueCountFrequency (%)
0 8
24.2%
12 3
 
9.1%
28 2
 
6.1%
43 1
 
3.0%
12,893 1
 
3.0%
5,420 1
 
3.0%
5,453 1
 
3.0%
94 1
 
3.0%
33 1
 
3.0%
7 1
 
3.0%
Other values (13) 13
39.4%
2024-02-10T10:08:29.804307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 12
15.8%
1 12
15.8%
2 11
14.5%
3 7
9.2%
4 6
7.9%
9 6
7.9%
8 5
6.6%
5 5
6.6%
, 4
 
5.3%
7 3
 
3.9%
Other values (4) 5
6.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 69
90.8%
Other Punctuation 4
 
5.3%
Other Letter 3
 
3.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 12
17.4%
1 12
17.4%
2 11
15.9%
3 7
10.1%
4 6
8.7%
9 6
8.7%
8 5
7.2%
5 5
7.2%
7 3
 
4.3%
6 2
 
2.9%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 73
96.1%
Hangul 3
 
3.9%

Most frequent character per script

Common
ValueCountFrequency (%)
0 12
16.4%
1 12
16.4%
2 11
15.1%
3 7
9.6%
4 6
8.2%
9 6
8.2%
8 5
6.8%
5 5
6.8%
, 4
 
5.5%
7 3
 
4.1%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 73
96.1%
Hangul 3
 
3.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 12
16.4%
1 12
16.4%
2 11
15.1%
3 7
9.6%
4 6
8.2%
9 6
8.2%
8 5
6.8%
5 5
6.8%
, 4
 
5.5%
7 3
 
4.1%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 10
Text

MISSING 

Distinct23
Distinct (%)67.6%
Missing1
Missing (%)2.9%
Memory size412.0 B
2024-02-10T10:08:30.379772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.2647059
Min length1

Characters and Unicode

Total characters77
Distinct characters21
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

Unique18 ?
Unique (%)52.9%

Sample

1st row출력일자 :
2nd row산수1동
3rd row4,415
4th row8,236
5th row64
ValueCountFrequency (%)
0 8
22.9%
21 2
 
5.7%
35 2
 
5.7%
64 2
 
5.7%
11 2
 
5.7%
6 2
 
5.7%
출력일자 1
 
2.9%
80 1
 
2.9%
4,404 1
 
2.9%
37 1
 
2.9%
Other values (13) 13
37.1%
2024-02-10T10:08:31.219052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 13
16.9%
0 10
13.0%
4 8
10.4%
6 6
7.8%
2 6
7.8%
3 6
7.8%
5 5
 
6.5%
8 4
 
5.2%
, 4
 
5.2%
9 3
 
3.9%
Other values (11) 12
15.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 62
80.5%
Other Letter 7
 
9.1%
Other Punctuation 5
 
6.5%
Dash Punctuation 2
 
2.6%
Space Separator 1
 
1.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 13
21.0%
0 10
16.1%
4 8
12.9%
6 6
9.7%
2 6
9.7%
3 6
9.7%
5 5
 
8.1%
8 4
 
6.5%
9 3
 
4.8%
7 1
 
1.6%
Other Letter
ValueCountFrequency (%)
1
14.3%
1
14.3%
1
14.3%
1
14.3%
1
14.3%
1
14.3%
1
14.3%
Other Punctuation
ValueCountFrequency (%)
, 4
80.0%
: 1
 
20.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 70
90.9%
Hangul 7
 
9.1%

Most frequent character per script

Common
ValueCountFrequency (%)
1 13
18.6%
0 10
14.3%
4 8
11.4%
6 6
8.6%
2 6
8.6%
3 6
8.6%
5 5
 
7.1%
8 4
 
5.7%
, 4
 
5.7%
9 3
 
4.3%
Other values (4) 5
 
7.1%
Hangul
ValueCountFrequency (%)
1
14.3%
1
14.3%
1
14.3%
1
14.3%
1
14.3%
1
14.3%
1
14.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 70
90.9%
Hangul 7
 
9.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 13
18.6%
0 10
14.3%
4 8
11.4%
6 6
8.6%
2 6
8.6%
3 6
8.6%
5 5
 
7.1%
8 4
 
5.7%
, 4
 
5.7%
9 3
 
4.3%
Other values (4) 5
 
7.1%
Hangul
ValueCountFrequency (%)
1
14.3%
1
14.3%
1
14.3%
1
14.3%
1
14.3%
1
14.3%
1
14.3%

Unnamed: 11
Text

MISSING 

Distinct23
Distinct (%)69.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T10:08:31.620657image/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

Unique20 ?
Unique (%)60.6%

Sample

1st row산수2동
2nd row4,749
3rd row10,127
4th row30
5th row6
ValueCountFrequency (%)
0 8
24.2%
30 3
 
9.1%
6 2
 
6.1%
3 1
 
3.0%
55 1
 
3.0%
4,741 1
 
3.0%
50 1
 
3.0%
8 1
 
3.0%
9 1
 
3.0%
40 1
 
3.0%
Other values (13) 13
39.4%
2024-02-10T10:08:32.458218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 17
23.6%
1 8
11.1%
3 7
9.7%
5 7
9.7%
4 6
 
8.3%
7 5
 
6.9%
9 4
 
5.6%
, 4
 
5.6%
2 4
 
5.6%
6 3
 
4.2%
Other values (5) 7
9.7%

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 (%)
0 17
27.0%
1 8
12.7%
3 7
11.1%
5 7
11.1%
4 6
 
9.5%
7 5
 
7.9%
9 4
 
6.3%
2 4
 
6.3%
6 3
 
4.8%
8 2
 
3.2%
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 69
95.8%
Hangul 3
 
4.2%

Most frequent character per script

Common
ValueCountFrequency (%)
0 17
24.6%
1 8
11.6%
3 7
10.1%
5 7
10.1%
4 6
 
8.7%
7 5
 
7.2%
9 4
 
5.8%
, 4
 
5.8%
2 4
 
5.8%
6 3
 
4.3%
Other values (2) 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 (%)
0 17
24.6%
1 8
11.6%
3 7
10.1%
5 7
10.1%
4 6
 
8.7%
7 5
 
7.2%
9 4
 
5.8%
, 4
 
5.8%
2 4
 
5.8%
6 3
 
4.3%
Other values (2) 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
Minimum2023-02-06 00:00:00
Maximum2023-02-06 00:00:00
2024-02-10T10:08:32.807802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-10T10:08:33.104149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Unnamed: 13
Text

MISSING 

Distinct26
Distinct (%)78.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T10:08:33.530907image/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 row지산1동
2nd row2,451
3rd row4,156
4th row42
5th row3
ValueCountFrequency (%)
0 7
21.2%
3 2
 
6.1%
46 1
 
3.0%
4,126 1
 
3.0%
2,429 1
 
3.0%
2 1
 
3.0%
30 1
 
3.0%
22 1
 
3.0%
6 1
 
3.0%
38 1
 
3.0%
Other values (16) 16
48.5%
2024-02-10T10:08:34.575391image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 12
16.9%
0 9
12.7%
4 9
12.7%
3 7
9.9%
1 7
9.9%
6 6
8.5%
5 5
7.0%
, 4
 
5.6%
9 3
 
4.2%
- 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 (%)
2 12
19.7%
0 9
14.8%
4 9
14.8%
3 7
11.5%
1 7
11.5%
6 6
9.8%
5 5
8.2%
9 3
 
4.9%
8 2
 
3.3%
7 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 (%)
2 12
17.6%
0 9
13.2%
4 9
13.2%
3 7
10.3%
1 7
10.3%
6 6
8.8%
5 5
7.4%
, 4
 
5.9%
9 3
 
4.4%
- 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 (%)
2 12
17.6%
0 9
13.2%
4 9
13.2%
3 7
10.3%
1 7
10.3%
6 6
8.8%
5 5
7.4%
, 4
 
5.9%
9 3
 
4.4%
- 3
 
4.4%
Other values (2) 3
 
4.4%
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
2024-02-10T10:08:34.925831image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
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

Unique21 ?
Unique (%)63.6%

Sample

1st row지산2동
2nd row2,373
3rd row4,389
4th row11
5th row6
ValueCountFrequency (%)
0 8
24.2%
2,373 2
 
6.1%
1 2
 
6.1%
6 2
 
6.1%
71 1
 
3.0%
31 1
 
3.0%
4,389 1
 
3.0%
40 1
 
3.0%
4,380 1
 
3.0%
9 1
 
3.0%
Other values (13) 13
39.4%
2024-02-10T10:08:35.879239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 11
16.2%
3 11
16.2%
1 9
13.2%
2 8
11.8%
4 5
7.4%
, 4
 
5.9%
6 4
 
5.9%
9 4
 
5.9%
7 3
 
4.4%
5 2
 
2.9%
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%
3 11
18.6%
1 9
15.3%
2 8
13.6%
4 5
8.5%
6 4
 
6.8%
9 4
 
6.8%
7 3
 
5.1%
5 2
 
3.4%
8 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%
3 11
16.9%
1 9
13.8%
2 8
12.3%
4 5
7.7%
, 4
 
6.2%
6 4
 
6.2%
9 4
 
6.2%
7 3
 
4.6%
5 2
 
3.1%
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%
3 11
16.9%
1 9
13.8%
2 8
12.3%
4 5
7.7%
, 4
 
6.2%
6 4
 
6.2%
9 4
 
6.2%
7 3
 
4.6%
5 2
 
3.1%
Other values (2) 4
 
6.2%
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
2024-02-10T10:08:36.307595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
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

Unique20 ?
Unique (%)60.6%

Sample

1st row서남동
2nd row2,233
3rd row2,981
4th row54
5th row3
ValueCountFrequency (%)
0 9
27.3%
3 2
 
6.1%
31 2
 
6.1%
56 1
 
3.0%
54 1
 
3.0%
2,981 1
 
3.0%
2,949 1
 
3.0%
2,210 1
 
3.0%
1 1
 
3.0%
32 1
 
3.0%
Other values (13) 13
39.4%
2024-02-10T10:08:37.153486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 11
15.9%
2 11
15.9%
3 9
13.0%
5 8
11.6%
1 7
10.1%
4 4
 
5.8%
, 4
 
5.8%
8 3
 
4.3%
6 3
 
4.3%
9 3
 
4.3%
Other values (5) 6
8.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 60
87.0%
Other Punctuation 4
 
5.8%
Other Letter 3
 
4.3%
Dash Punctuation 2
 
2.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 11
18.3%
2 11
18.3%
3 9
15.0%
5 8
13.3%
1 7
11.7%
4 4
 
6.7%
8 3
 
5.0%
6 3
 
5.0%
9 3
 
5.0%
7 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 66
95.7%
Hangul 3
 
4.3%

Most frequent character per script

Common
ValueCountFrequency (%)
0 11
16.7%
2 11
16.7%
3 9
13.6%
5 8
12.1%
1 7
10.6%
4 4
 
6.1%
, 4
 
6.1%
8 3
 
4.5%
6 3
 
4.5%
9 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 66
95.7%
Hangul 3
 
4.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 11
16.7%
2 11
16.7%
3 9
13.6%
5 8
12.1%
1 7
10.6%
4 4
 
6.1%
, 4
 
6.1%
8 3
 
4.5%
6 3
 
4.5%
9 3
 
4.5%
Other values (2) 3
 
4.5%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 16
Text

MISSING 

Distinct25
Distinct (%)75.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T10:08:37.546196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
Mean length2.1818182
Min length1

Characters and Unicode

Total characters72
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

Unique20 ?
Unique (%)60.6%

Sample

1st row학동
2nd row3,559
3rd row7,493
4th row103
5th row9
ValueCountFrequency (%)
0 5
 
15.2%
27 2
 
6.1%
70 2
 
6.1%
1 2
 
6.1%
9 2
 
6.1%
6 1
 
3.0%
140 1
 
3.0%
7,436 1
 
3.0%
3,539 1
 
3.0%
13 1
 
3.0%
Other values (15) 15
45.5%
2024-02-10T10:08:38.526370image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 11
15.3%
7 9
12.5%
3 9
12.5%
5 9
12.5%
9 7
9.7%
1 6
8.3%
4 6
8.3%
, 4
 
5.6%
2 3
 
4.2%
- 3
 
4.2%
Other values (4) 5
6.9%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 11
17.5%
7 9
14.3%
3 9
14.3%
5 9
14.3%
9 7
11.1%
1 6
9.5%
4 6
9.5%
2 3
 
4.8%
6 2
 
3.2%
8 1
 
1.6%
Other Letter
ValueCountFrequency (%)
1
50.0%
1
50.0%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 70
97.2%
Hangul 2
 
2.8%

Most frequent character per script

Common
ValueCountFrequency (%)
0 11
15.7%
7 9
12.9%
3 9
12.9%
5 9
12.9%
9 7
10.0%
1 6
8.6%
4 6
8.6%
, 4
 
5.7%
2 3
 
4.3%
- 3
 
4.3%
Other values (2) 3
 
4.3%
Hangul
ValueCountFrequency (%)
1
50.0%
1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 70
97.2%
Hangul 2
 
2.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 11
15.7%
7 9
12.9%
3 9
12.9%
5 9
12.9%
9 7
10.0%
1 6
8.6%
4 6
8.6%
, 4
 
5.7%
2 3
 
4.3%
- 3
 
4.3%
Other values (2) 3
 
4.3%
Hangul
ValueCountFrequency (%)
1
50.0%
1
50.0%

Unnamed: 17
Text

MISSING 

Distinct27
Distinct (%)81.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T10:08:38.889652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length2
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

Unique25 ?
Unique (%)75.8%

Sample

1st row학운동
2nd row5,222
3rd row11,226
4th row42
5th row18
ValueCountFrequency (%)
0 6
 
18.2%
16 2
 
6.1%
1 2
 
6.1%
45 1
 
3.0%
32 1
 
3.0%
44 1
 
3.0%
11,210 1
 
3.0%
5,219 1
 
3.0%
2 1
 
3.0%
3 1
 
3.0%
Other values (16) 16
48.5%
2024-02-10T10:08:39.577074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 15
20.5%
2 12
16.4%
0 8
11.0%
3 6
 
8.2%
5 5
 
6.8%
4 5
 
6.8%
7 4
 
5.5%
, 4
 
5.5%
9 4
 
5.5%
6 3
 
4.1%
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 (%)
1 15
23.4%
2 12
18.8%
0 8
12.5%
3 6
 
9.4%
5 5
 
7.8%
4 5
 
7.8%
7 4
 
6.2%
9 4
 
6.2%
6 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 (%)
- 2
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
1 15
21.4%
2 12
17.1%
0 8
11.4%
3 6
 
8.6%
5 5
 
7.1%
4 5
 
7.1%
7 4
 
5.7%
, 4
 
5.7%
9 4
 
5.7%
6 3
 
4.3%
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 (%)
1 15
21.4%
2 12
17.1%
0 8
11.4%
3 6
 
8.6%
5 5
 
7.1%
4 5
 
7.1%
7 4
 
5.7%
, 4
 
5.7%
9 4
 
5.7%
6 3
 
4.3%
Other values (2) 4
 
5.7%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 18
Text

MISSING 

Distinct22
Distinct (%)66.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T10:08:39.980919image/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

Unique18 ?
Unique (%)54.5%

Sample

1st row지원1동
2nd row4,196
3rd row9,006
4th row21
5th row8
ValueCountFrequency (%)
0 9
27.3%
21 2
 
6.1%
8 2
 
6.1%
4,196 2
 
6.1%
35 1
 
3.0%
89 1
 
3.0%
12 1
 
3.0%
10 1
 
3.0%
38 1
 
3.0%
28 1
 
3.0%
Other values (12) 12
36.4%
2024-02-10T10:08:40.882550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 13
18.8%
2 8
11.6%
4 7
10.1%
1 7
10.1%
9 7
10.1%
8 7
10.1%
6 5
 
7.2%
3 5
 
7.2%
, 4
 
5.8%
7 1
 
1.4%
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 (%)
0 13
21.3%
2 8
13.1%
4 7
11.5%
1 7
11.5%
9 7
11.5%
8 7
11.5%
6 5
 
8.2%
3 5
 
8.2%
7 1
 
1.6%
5 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 (%)
0 13
19.7%
2 8
12.1%
4 7
10.6%
1 7
10.6%
9 7
10.6%
8 7
10.6%
6 5
 
7.6%
3 5
 
7.6%
, 4
 
6.1%
7 1
 
1.5%
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 (%)
0 13
19.7%
2 8
12.1%
4 7
10.6%
1 7
10.6%
9 7
10.6%
8 7
10.6%
6 5
 
7.6%
3 5
 
7.6%
, 4
 
6.1%
7 1
 
1.5%
Other values (2) 2
 
3.0%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 19
Text

MISSING 

Distinct25
Distinct (%)75.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T10:08:41.259478image/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 row지원2동
2nd row7,268
3rd row16,075
4th row110
5th row6
ValueCountFrequency (%)
0 7
21.2%
12 2
 
6.1%
105 2
 
6.1%
163 1
 
3.0%
85 1
 
3.0%
108 1
 
3.0%
16,123 1
 
3.0%
7,273 1
 
3.0%
2 1
 
3.0%
48 1
 
3.0%
Other values (15) 15
45.5%
2024-02-10T10:08:42.063347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 14
17.7%
1 14
17.7%
2 9
11.4%
7 7
8.9%
6 7
8.9%
8 6
7.6%
5 5
 
6.3%
3 5
 
6.3%
, 4
 
5.1%
9 2
 
2.5%
Other values (5) 6
7.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 71
89.9%
Other Punctuation 4
 
5.1%
Other Letter 3
 
3.8%
Dash Punctuation 1
 
1.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 14
19.7%
1 14
19.7%
2 9
12.7%
7 7
9.9%
6 7
9.9%
8 6
8.5%
5 5
 
7.0%
3 5
 
7.0%
9 2
 
2.8%
4 2
 
2.8%
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 76
96.2%
Hangul 3
 
3.8%

Most frequent character per script

Common
ValueCountFrequency (%)
0 14
18.4%
1 14
18.4%
2 9
11.8%
7 7
9.2%
6 7
9.2%
8 6
7.9%
5 5
 
6.6%
3 5
 
6.6%
, 4
 
5.3%
9 2
 
2.6%
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 (%)
0 14
18.4%
1 14
18.4%
2 9
11.8%
7 7
9.2%
6 7
9.2%
8 6
7.9%
5 5
 
6.6%
3 5
 
6.6%
, 4
 
5.3%
9 2
 
2.6%
Other values (2) 3
 
3.9%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Correlations

2024-02-10T10:08:42.488043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
인구이동보고서(1호)Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 6Unnamed: 7Unnamed: 8Unnamed: 9Unnamed: 10Unnamed: 11Unnamed: 13Unnamed: 14Unnamed: 15Unnamed: 16Unnamed: 17Unnamed: 18Unnamed: 19
인구이동보고서(1호)1.0000.0001.000NaN1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
Unnamed: 20.0001.000NaNNaN0.9721.0001.0001.0001.0001.0001.0001.0001.0001.0000.9720.9201.0001.000
Unnamed: 31.000NaN1.000NaN1.0001.0001.0001.0001.0000.8541.0001.0001.0001.0000.5831.0001.0000.790
Unnamed: 4NaNNaNNaN1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0000.0001.0001.0001.0001.000
Unnamed: 51.0000.9721.0001.0001.0000.9930.9930.9920.9950.9940.9920.9940.9870.9940.9950.9980.9910.995
Unnamed: 61.0001.0001.0001.0000.9931.0000.9970.9930.9910.9920.9911.0000.9930.9930.9870.9970.9900.989
Unnamed: 71.0001.0001.0001.0000.9930.9971.0000.9900.9870.9880.9901.0000.9970.9950.9891.0000.9860.989
Unnamed: 81.0001.0001.0001.0000.9920.9930.9901.0000.9990.9961.0001.0000.9760.9950.9850.9960.9950.988
Unnamed: 91.0001.0001.0001.0000.9950.9910.9870.9991.0000.9950.9991.0000.9760.9950.9880.9960.9950.988
Unnamed: 101.0001.0000.8541.0000.9940.9920.9880.9960.9951.0000.9951.0000.9720.9790.9860.9960.9980.986
Unnamed: 111.0001.0001.0001.0000.9920.9910.9901.0000.9990.9951.0001.0000.9760.9940.9850.9960.9950.988
Unnamed: 131.0001.0001.0001.0000.9941.0001.0001.0001.0001.0001.0001.0000.9941.0000.9950.9971.0000.995
Unnamed: 141.0001.0001.0001.0000.9870.9930.9970.9760.9760.9720.9760.9941.0000.9870.9800.9940.9940.974
Unnamed: 151.0001.0001.0000.0000.9940.9930.9950.9950.9950.9790.9941.0000.9871.0000.9881.0000.9760.992
Unnamed: 161.0000.9720.5831.0000.9950.9870.9890.9850.9880.9860.9850.9950.9800.9881.0000.9910.9830.994
Unnamed: 171.0000.9201.0001.0000.9980.9971.0000.9960.9960.9960.9960.9970.9941.0000.9911.0000.9960.997
Unnamed: 181.0001.0001.0001.0000.9910.9900.9860.9950.9950.9980.9951.0000.9940.9760.9830.9961.0000.983
Unnamed: 191.0001.0000.7901.0000.9950.9890.9890.9880.9880.9860.9880.9950.9740.9920.9940.9970.9831.000

Missing values

2024-02-10T10:08:14.380532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-02-10T10:08:15.402828image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2024-02-10T10:08:16.212567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

Unnamed: 0인구이동보고서(1호)Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 6Unnamed: 7Unnamed: 8Unnamed: 9Unnamed: 10Unnamed: 11Unnamed: 12Unnamed: 13Unnamed: 14Unnamed: 15Unnamed: 16Unnamed: 17Unnamed: 18Unnamed: 19
0<NA>행정기관 :<NA>광주광역시 동구<NA><NA><NA><NA><NA><NA>출력일자 :<NA>2023.02.06<NA><NA><NA><NA><NA><NA><NA>
1<NA>작성기준 :<NA>2023.01 현재<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 계충장동동명동계림1동계림2동산수1동산수2동<NA>지산1동지산2동서남동학동학운동지원1동지원2동
3<NA>전월말세대수<NA><NA><NA>54,0723,9652,4265,7955,4204,4154,749<NA>2,4512,3732,2333,5595,2224,1967,268
4<NA>전월말인구수<NA><NA><NA>105,9095,0773,74310,50712,8938,23610,127<NA>4,1564,3892,9817,49311,2269,00616,075
5<NA>전월말거주불명자수<NA><NA><NA>7383611879286430<NA>4211541034221110
6<NA>전월말재외국민등록자수<NA><NA><NA>10377121266<NA>36391886
7<NA>증 가 요 인전 입<NA>1,378165771661965265<NA>646582797483210
8<NA><NA><NA>남자<NA>683743786912135<NA>353646353547105
9<NA><NA><NA>여자<NA>6959140801053130<NA>292936443936105
Unnamed: 0인구이동보고서(1호)Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 6Unnamed: 7Unnamed: 8Unnamed: 9Unnamed: 10Unnamed: 11Unnamed: 12Unnamed: 13Unnamed: 14Unnamed: 15Unnamed: 16Unnamed: 17Unnamed: 18Unnamed: 19
25<NA><NA>말소<NA><NA>0000000<NA>0000000
26<NA><NA>국외<NA><NA>0000000<NA>0000000
27<NA><NA>기타<NA><NA>0000000<NA>0000000
28<NA>세대수증감<NA><NA><NA>2271-7733-11-8<NA>-220-23-20-305
29<NA>인구수증감<NA><NA><NA>-2280-181794-37-50<NA>-30-9-32-57-16-1248
30<NA>거주불명자수증감<NA><NA><NA>-133-10000<NA>-2-11-1320-2
31<NA>금월말세대수<NA><NA><NA>54,0944,0362,4195,8025,4534,4044,741<NA>2,4292,3732,2103,5395,2194,1967,273
32<NA>금월말인구수<NA><NA><NA>105,8875,1573,72510,52412,9878,19910,077<NA>4,1264,3802,9497,43611,2108,99416,123
33<NA>금월말거주불명자수<NA><NA><NA>7253911779286430<NA>401055904421108
34<NA>금월말재외국민등록자수<NA><NA><NA>10577121266<NA>36391987

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: 19# duplicates
0<NA>기타<NA><NA>0000000<NA>00000002