Overview

Dataset statistics

Number of variables20
Number of observations35
Missing cells193
Missing cells (%)27.6%
Duplicate rows2
Duplicate rows (%)5.7%
Total size in memory5.6 KiB
Average record size in memory164.8 B

Variable types

Unsupported1
Text18
DateTime1

Dataset

Description2023-04-14
Author주민등록인구통계
URLhttps://bigdata.gwangju.go.kr/usr/dataSet/getDataDetailView.rd?dataSetUncd=DS000201926

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: 0 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-02-10 10:09:24.671786
Analysis finished2024-02-10 10:09:33.045688
Duration8.37 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

인구이동보고서(1호)
Text

MISSING 

Distinct16
Distinct (%)100.0%
Missing19
Missing (%)54.3%
Memory size412.0 B
2024-02-10T10:09:33.258234image/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 (%)
요 2
 
7.7%
인 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%
소 1
 
3.8%
Other values (13) 13
50.0%
2024-02-10T10:09:34.272089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
12
 
9.5%
수 11
 
8.7%
말 8
 
6.3%
월 8
 
6.3%
인 5
 
4.0%
자 5
 
4.0%
전 4
 
3.2%
감 4
 
3.2%
증 4
 
3.2%
금 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 (%)
수 11
 
10.6%
말 8
 
7.7%
월 8
 
7.7%
인 5
 
4.8%
자 5
 
4.8%
전 4
 
3.8%
감 4
 
3.8%
증 4
 
3.8%
금 4
 
3.8%
구 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 (%)
수 11
 
10.6%
말 8
 
7.7%
월 8
 
7.7%
인 5
 
4.8%
자 5
 
4.8%
전 4
 
3.8%
감 4
 
3.8%
증 4
 
3.8%
금 4
 
3.8%
구 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 (%)
수 11
 
10.6%
말 8
 
7.7%
월 8
 
7.7%
인 5
 
4.8%
자 5
 
4.8%
전 4
 
3.8%
감 4
 
3.8%
증 4
 
3.8%
금 4
 
3.8%
구 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
2024-02-10T10:09:34.890774image/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%
전 2
15.4%
입 1
7.7%
복귀 1
7.7%
출생 1
7.7%
등록 1
7.7%
출 1
7.7%
사망 1
7.7%
말소 1
7.7%
2024-02-10T10:09:35.712546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4
15.4%
국 2
 
7.7%
기 2
 
7.7%
타 2
 
7.7%
전 2
 
7.7%
외 2
 
7.7%
출 2
 
7.7%
록 1
 
3.8%
말 1
 
3.8%
망 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 (%)
국 2
 
9.1%
기 2
 
9.1%
타 2
 
9.1%
전 2
 
9.1%
외 2
 
9.1%
출 2
 
9.1%
록 1
 
4.5%
말 1
 
4.5%
망 1
 
4.5%
사 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 (%)
국 2
 
9.1%
기 2
 
9.1%
타 2
 
9.1%
전 2
 
9.1%
외 2
 
9.1%
출 2
 
9.1%
록 1
 
4.5%
말 1
 
4.5%
망 1
 
4.5%
사 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 (%)
국 2
 
9.1%
기 2
 
9.1%
타 2
 
9.1%
전 2
 
9.1%
외 2
 
9.1%
출 2
 
9.1%
록 1
 
4.5%
말 1
 
4.5%
망 1
 
4.5%
사 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
2024-02-10T10:09:36.078646image/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 동구
2nd row2023.03 현재
3rd row계
4th row남자
5th row여자
ValueCountFrequency (%)
계 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%
2023.03 1
7.1%
현재 1
7.1%
2024-02-10T10:09:36.927523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
시 5
 
12.2%
자 4
 
9.8%
도 4
 
9.8%
3
 
7.3%
계 2
 
4.9%
0 2
 
4.9%
여 2
 
4.9%
내 2
 
4.9%
간 2
 
4.9%
광 2
 
4.9%
Other values (10) 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 (%)
시 5
16.1%
자 4
12.9%
도 4
12.9%
계 2
 
6.5%
여 2
 
6.5%
내 2
 
6.5%
간 2
 
6.5%
광 2
 
6.5%
남 2
 
6.5%
현 1
 
3.2%
Other values (5) 5
16.1%
Decimal Number
ValueCountFrequency (%)
0 2
33.3%
3 2
33.3%
2 2
33.3%
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 (%)
시 5
16.1%
자 4
12.9%
도 4
12.9%
계 2
 
6.5%
여 2
 
6.5%
내 2
 
6.5%
간 2
 
6.5%
광 2
 
6.5%
남 2
 
6.5%
현 1
 
3.2%
Other values (5) 5
16.1%
Common
ValueCountFrequency (%)
3
30.0%
0 2
20.0%
3 2
20.0%
2 2
20.0%
. 1
 
10.0%

Most occurring blocks

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

Most frequent character per block

Hangul
ValueCountFrequency (%)
시 5
16.1%
자 4
12.9%
도 4
12.9%
계 2
 
6.5%
여 2
 
6.5%
내 2
 
6.5%
간 2
 
6.5%
광 2
 
6.5%
남 2
 
6.5%
현 1
 
3.2%
Other values (5) 5
16.1%
ASCII
ValueCountFrequency (%)
3
30.0%
0 2
20.0%
3 2
20.0%
2 2
20.0%
. 1
 
10.0%

Unnamed: 4
Text

MISSING 

Distinct2
Distinct (%)50.0%
Missing31
Missing (%)88.6%
Memory size412.0 B
2024-02-10T10:09:37.213138image/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%
2024-02-10T10:09:37.867508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
시 4
25.0%
군 4
25.0%
구 4
25.0%
내 2
12.5%
간 2
12.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 16
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 4
25.0%
군 4
25.0%
구 4
25.0%
내 2
12.5%
간 2
12.5%

Most occurring scripts

ValueCountFrequency (%)
Hangul 16
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 4
25.0%
군 4
25.0%
구 4
25.0%
내 2
12.5%
간 2
12.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 16
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
시 4
25.0%
군 4
25.0%
구 4
25.0%
내 2
12.5%
간 2
12.5%

Unnamed: 5
Text

MISSING 

Distinct27
Distinct (%)81.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T10:09:38.235686image/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

Unique25 ?
Unique (%)75.8%

Sample

1st row합 계
2nd row54,342
3rd row106,101
4th row707
5th row107
ValueCountFrequency (%)
0 6
 
17.6%
395 2
 
5.9%
844 1
 
2.9%
705 1
 
2.9%
106,247 1
 
2.9%
54,507 1
 
2.9%
2 1
 
2.9%
146 1
 
2.9%
165 1
 
2.9%
1 1
 
2.9%
Other values (18) 18
52.9%
2024-02-10T10:09:38.936128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 17
16.8%
0 16
15.8%
1 12
11.9%
7 10
9.9%
6 8
7.9%
4 7
6.9%
, 6
 
5.9%
2 6
 
5.9%
8 6
 
5.9%
9 5
 
5.0%
Other values (5) 8
7.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 90
89.1%
Other Punctuation 6
 
5.9%
Space Separator 2
 
2.0%
Other Letter 2
 
2.0%
Dash Punctuation 1
 
1.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 17
18.9%
0 16
17.8%
1 12
13.3%
7 10
11.1%
6 8
8.9%
4 7
7.8%
2 6
 
6.7%
8 6
 
6.7%
9 5
 
5.6%
3 3
 
3.3%
Other Letter
ValueCountFrequency (%)
합 1
50.0%
계 1
50.0%
Other Punctuation
ValueCountFrequency (%)
, 6
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
5 17
17.2%
0 16
16.2%
1 12
12.1%
7 10
10.1%
6 8
8.1%
4 7
7.1%
, 6
 
6.1%
2 6
 
6.1%
8 6
 
6.1%
9 5
 
5.1%
Other values (3) 6
 
6.1%
Hangul
ValueCountFrequency (%)
합 1
50.0%
계 1
50.0%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 17
17.2%
0 16
16.2%
1 12
12.1%
7 10
10.1%
6 8
8.1%
4 7
7.1%
, 6
 
6.1%
2 6
 
6.1%
8 6
 
6.1%
9 5
 
5.1%
Other values (3) 6
 
6.1%
Hangul
ValueCountFrequency (%)
합 1
50.0%
계 1
50.0%

Unnamed: 6
Text

MISSING 

Distinct23
Distinct (%)69.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T10:09:39.190508image/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

Unique19 ?
Unique (%)57.6%

Sample

1st row충장동
2nd row4,087
3rd row5,213
4th row38
5th row7
ValueCountFrequency (%)
0 8
24.2%
73 2
 
6.1%
66 2
 
6.1%
1 2
 
6.1%
5,213 2
 
6.1%
141 1
 
3.0%
29 1
 
3.0%
38 1
 
3.0%
68 1
 
3.0%
37 1
 
3.0%
Other values (12) 12
36.4%
2024-02-10T10:09:39.987022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

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

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 11
18.0%
1 11
18.0%
3 8
13.1%
6 7
11.5%
7 6
9.8%
4 6
9.8%
8 4
 
6.6%
5 3
 
4.9%
2 3
 
4.9%
9 2
 
3.3%
Other Letter
ValueCountFrequency (%)
충 1
33.3%
장 1
33.3%
동 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 11
16.7%
1 11
16.7%
3 8
12.1%
6 7
10.6%
7 6
9.1%
4 6
9.1%
, 4
 
6.1%
8 4
 
6.1%
5 3
 
4.5%
2 3
 
4.5%
Other values (2) 3
 
4.5%
Hangul
ValueCountFrequency (%)
충 1
33.3%
장 1
33.3%
동 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%
1 11
16.7%
3 8
12.1%
6 7
10.6%
7 6
9.1%
4 6
9.1%
, 4
 
6.1%
8 4
 
6.1%
5 3
 
4.5%
2 3
 
4.5%
Other values (2) 3
 
4.5%
Hangul
ValueCountFrequency (%)
충 1
33.3%
장 1
33.3%
동 1
33.3%

Unnamed: 7
Text

MISSING 

Distinct19
Distinct (%)57.6%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T10:09:40.304952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
Mean length2.0606061
Min length1

Characters and Unicode

Total characters68
Distinct characters14
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique14 ?
Unique (%)42.4%

Sample

1st row동명동
2nd row2,440
3rd row3,733
4th row115
5th row8
ValueCountFrequency (%)
0 9
27.3%
31 3
 
9.1%
7 3
 
9.1%
22 2
 
6.1%
115 2
 
6.1%
3,733 1
 
3.0%
8 1
 
3.0%
67 1
 
3.0%
36 1
 
3.0%
18 1
 
3.0%
Other values (9) 9
27.3%
2024-02-10T10:09:41.094047image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 10
14.7%
3 9
13.2%
1 9
13.2%
7 8
11.8%
2 8
11.8%
4 5
7.4%
6 4
 
5.9%
, 4
 
5.9%
8 3
 
4.4%
5 2
 
2.9%
Other values (4) 6
8.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 60
88.2%
Other Punctuation 4
 
5.9%
Other Letter 3
 
4.4%
Dash Punctuation 1
 
1.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 10
16.7%
3 9
15.0%
1 9
15.0%
7 8
13.3%
2 8
13.3%
4 5
8.3%
6 4
 
6.7%
8 3
 
5.0%
5 2
 
3.3%
9 2
 
3.3%
Other Letter
ValueCountFrequency (%)
동 2
66.7%
명 1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
0 10
15.4%
3 9
13.8%
1 9
13.8%
7 8
12.3%
2 8
12.3%
4 5
7.7%
6 4
 
6.2%
, 4
 
6.2%
8 3
 
4.6%
5 2
 
3.1%
Other values (2) 3
 
4.6%
Hangul
ValueCountFrequency (%)
동 2
66.7%
명 1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 10
15.4%
3 9
13.8%
1 9
13.8%
7 8
12.3%
2 8
12.3%
4 5
7.7%
6 4
 
6.2%
, 4
 
6.2%
8 3
 
4.6%
5 2
 
3.1%
Other values (2) 3
 
4.6%
Hangul
ValueCountFrequency (%)
동 2
66.7%
명 1
33.3%

Unnamed: 8
Text

MISSING 

Distinct24
Distinct (%)72.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T10:09:41.410388image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length2
Mean length2.2727273
Min length1

Characters and Unicode

Total characters75
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 row계림1동
2nd row5,812
3rd row10,568
4th row76
5th row12
ValueCountFrequency (%)
0 7
21.2%
12 2
 
6.1%
13 2
 
6.1%
76 2
 
6.1%
39 1
 
3.0%
10,568 1
 
3.0%
173 1
 
3.0%
10,581 1
 
3.0%
5,823 1
 
3.0%
1 1
 
3.0%
Other values (14) 14
42.4%
2024-02-10T10:09:42.178775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 14
18.7%
0 10
13.3%
7 9
12.0%
2 6
8.0%
5 6
8.0%
6 5
 
6.7%
3 5
 
6.7%
8 5
 
6.7%
9 4
 
5.3%
4 4
 
5.3%
Other values (4) 7
9.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 68
90.7%
Other Punctuation 4
 
5.3%
Other Letter 3
 
4.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 14
20.6%
0 10
14.7%
7 9
13.2%
2 6
8.8%
5 6
8.8%
6 5
 
7.4%
3 5
 
7.4%
8 5
 
7.4%
9 4
 
5.9%
4 4
 
5.9%
Other Letter
ValueCountFrequency (%)
계 1
33.3%
림 1
33.3%
동 1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
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 10
13.9%
7 9
12.5%
2 6
8.3%
5 6
8.3%
6 5
 
6.9%
3 5
 
6.9%
8 5
 
6.9%
9 4
 
5.6%
4 4
 
5.6%
Hangul
ValueCountFrequency (%)
계 1
33.3%
림 1
33.3%
동 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 10
13.9%
7 9
12.5%
2 6
8.3%
5 6
8.3%
6 5
 
6.9%
3 5
 
6.9%
8 5
 
6.9%
9 4
 
5.6%
4 4
 
5.6%
Hangul
ValueCountFrequency (%)
계 1
33.3%
림 1
33.3%
동 1
33.3%

Unnamed: 9
Text

MISSING 

Distinct24
Distinct (%)72.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T10:09:42.512389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
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

Unique21 ?
Unique (%)63.6%

Sample

1st row계림2동
2nd row5,477
3rd row13,043
4th row28
5th row12
ValueCountFrequency (%)
0 8
24.2%
28 2
 
6.1%
12 2
 
6.1%
50 1
 
3.0%
13,043 1
 
3.0%
127 1
 
3.0%
5,456 1
 
3.0%
64 1
 
3.0%
21 1
 
3.0%
8 1
 
3.0%
Other values (14) 14
42.4%
2024-02-10T10:09:43.173887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 12
14.8%
2 12
14.8%
0 10
12.3%
3 8
9.9%
9 6
7.4%
4 6
7.4%
5 5
6.2%
6 5
6.2%
8 4
 
4.9%
, 4
 
4.9%
Other values (5) 9
11.1%

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 12
16.7%
2 12
16.7%
0 10
13.9%
3 8
11.1%
9 6
8.3%
4 6
8.3%
5 5
6.9%
6 5
6.9%
8 4
 
5.6%
7 4
 
5.6%
Other Letter
ValueCountFrequency (%)
계 1
33.3%
림 1
33.3%
동 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 12
15.4%
2 12
15.4%
0 10
12.8%
3 8
10.3%
9 6
7.7%
4 6
7.7%
5 5
6.4%
6 5
6.4%
8 4
 
5.1%
, 4
 
5.1%
Other values (2) 6
7.7%
Hangul
ValueCountFrequency (%)
계 1
33.3%
림 1
33.3%
동 1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 12
15.4%
2 12
15.4%
0 10
12.8%
3 8
10.3%
9 6
7.7%
4 6
7.7%
5 5
6.4%
6 5
6.4%
8 4
 
5.1%
, 4
 
5.1%
Other values (2) 6
7.7%
Hangul
ValueCountFrequency (%)
계 1
33.3%
림 1
33.3%
동 1
33.3%

Unnamed: 10
Text

MISSING 

Distinct23
Distinct (%)67.6%
Missing1
Missing (%)2.9%
Memory size412.0 B
2024-02-10T10:09:43.509627image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.2352941
Min length1

Characters and Unicode

Total characters76
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

Unique19 ?
Unique (%)55.9%

Sample

1st row출력일자 :
2nd row산수1동
3rd row4,404
4th row8,191
5th row63
ValueCountFrequency (%)
0 9
25.7%
6 2
 
5.7%
8,191 2
 
5.7%
63 2
 
5.7%
56 1
 
2.9%
1
 
2.9%
출력일자 1
 
2.9%
7 1
 
2.9%
11 1
 
2.9%
5 1
 
2.9%
Other values (14) 14
40.0%
2024-02-10T10:09:44.292405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 14
18.4%
0 12
15.8%
4 8
10.5%
6 8
10.5%
3 7
9.2%
5 5
 
6.6%
, 4
 
5.3%
9 4
 
5.3%
8 2
 
2.6%
출 1
 
1.3%
Other values (11) 11
14.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 62
81.6%
Other Letter 7
 
9.2%
Other Punctuation 5
 
6.6%
Space Separator 1
 
1.3%
Dash Punctuation 1
 
1.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 14
22.6%
0 12
19.4%
4 8
12.9%
6 8
12.9%
3 7
11.3%
5 5
 
8.1%
9 4
 
6.5%
8 2
 
3.2%
7 1
 
1.6%
2 1
 
1.6%
Other Letter
ValueCountFrequency (%)
출 1
14.3%
자 1
14.3%
일 1
14.3%
력 1
14.3%
수 1
14.3%
동 1
14.3%
산 1
14.3%
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 69
90.8%
Hangul 7
 
9.2%

Most frequent character per script

Common
ValueCountFrequency (%)
1 14
20.3%
0 12
17.4%
4 8
11.6%
6 8
11.6%
3 7
10.1%
5 5
 
7.2%
, 4
 
5.8%
9 4
 
5.8%
8 2
 
2.9%
1
 
1.4%
Other values (4) 4
 
5.8%
Hangul
ValueCountFrequency (%)
출 1
14.3%
자 1
14.3%
일 1
14.3%
력 1
14.3%
수 1
14.3%
동 1
14.3%
산 1
14.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 69
90.8%
Hangul 7
 
9.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 14
20.3%
0 12
17.4%
4 8
11.6%
6 8
11.6%
3 7
10.1%
5 5
 
7.2%
, 4
 
5.8%
9 4
 
5.8%
8 2
 
2.9%
1
 
1.4%
Other values (4) 4
 
5.8%
Hangul
ValueCountFrequency (%)
출 1
14.3%
자 1
14.3%
일 1
14.3%
력 1
14.3%
수 1
14.3%
동 1
14.3%
산 1
14.3%

Unnamed: 11
Text

MISSING 

Distinct21
Distinct (%)63.6%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T10:09:44.608812image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
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

Unique16 ?
Unique (%)48.5%

Sample

1st row산수2동
2nd row4,729
3rd row10,017
4th row29
5th row6
ValueCountFrequency (%)
0 8
24.2%
29 3
 
9.1%
6 2
 
6.1%
42 2
 
6.1%
32 2
 
6.1%
5 2
 
6.1%
4,729 1
 
3.0%
87 1
 
3.0%
10,017 1
 
3.0%
45 1
 
3.0%
Other values (10) 10
30.3%
2024-02-10T10:09:45.478762image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 13
18.6%
0 12
17.1%
4 8
11.4%
9 5
 
7.1%
7 5
 
7.1%
1 5
 
7.1%
8 4
 
5.7%
, 4
 
5.7%
5 4
 
5.7%
3 3
 
4.3%
Other values (5) 7
10.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 61
87.1%
Other Punctuation 4
 
5.7%
Other Letter 3
 
4.3%
Dash Punctuation 2
 
2.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 13
21.3%
0 12
19.7%
4 8
13.1%
9 5
 
8.2%
7 5
 
8.2%
1 5
 
8.2%
8 4
 
6.6%
5 4
 
6.6%
3 3
 
4.9%
6 2
 
3.3%
Other Letter
ValueCountFrequency (%)
산 1
33.3%
수 1
33.3%
동 1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
2 13
19.4%
0 12
17.9%
4 8
11.9%
9 5
 
7.5%
7 5
 
7.5%
1 5
 
7.5%
8 4
 
6.0%
, 4
 
6.0%
5 4
 
6.0%
3 3
 
4.5%
Other values (2) 4
 
6.0%
Hangul
ValueCountFrequency (%)
산 1
33.3%
수 1
33.3%
동 1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 13
19.4%
0 12
17.9%
4 8
11.9%
9 5
 
7.5%
7 5
 
7.5%
1 5
 
7.5%
8 4
 
6.0%
, 4
 
6.0%
5 4
 
6.0%
3 3
 
4.5%
Other values (2) 4
 
6.0%
Hangul
ValueCountFrequency (%)
산 1
33.3%
수 1
33.3%
동 1
33.3%

Unnamed: 12
Date

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing34
Missing (%)97.1%
Memory size412.0 B
Minimum2023-04-03 00:00:00
Maximum2023-04-03 00:00:00
2024-02-10T10:09:45.868343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-10T10:09:46.155983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Unnamed: 13
Text

MISSING 

Distinct21
Distinct (%)63.6%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T10:09:46.414999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length2.0606061
Min length1

Characters and Unicode

Total characters68
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

Unique16 ?
Unique (%)48.5%

Sample

1st row지산1동
2nd row2,435
3rd row4,129
4th row41
5th row3
ValueCountFrequency (%)
0 8
24.2%
3 3
 
9.1%
21 2
 
6.1%
43 2
 
6.1%
41 2
 
6.1%
72 1
 
3.0%
29 1
 
3.0%
2,446 1
 
3.0%
11 1
 
3.0%
5 1
 
3.0%
Other values (11) 11
33.3%
2024-02-10T10:09:47.256709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 11
16.2%
4 11
16.2%
0 10
14.7%
2 9
13.2%
3 8
11.8%
5 6
8.8%
, 4
 
5.9%
9 3
 
4.4%
6 2
 
2.9%
지 1
 
1.5%
Other values (3) 3
 
4.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 61
89.7%
Other Punctuation 4
 
5.9%
Other Letter 3
 
4.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 11
18.0%
4 11
18.0%
0 10
16.4%
2 9
14.8%
3 8
13.1%
5 6
9.8%
9 3
 
4.9%
6 2
 
3.3%
7 1
 
1.6%
Other Letter
ValueCountFrequency (%)
지 1
33.3%
산 1
33.3%
동 1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
1 11
16.9%
4 11
16.9%
0 10
15.4%
2 9
13.8%
3 8
12.3%
5 6
9.2%
, 4
 
6.2%
9 3
 
4.6%
6 2
 
3.1%
7 1
 
1.5%
Hangul
ValueCountFrequency (%)
지 1
33.3%
산 1
33.3%
동 1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 11
16.9%
4 11
16.9%
0 10
15.4%
2 9
13.8%
3 8
12.3%
5 6
9.2%
, 4
 
6.2%
9 3
 
4.6%
6 2
 
3.1%
7 1
 
1.5%
Hangul
ValueCountFrequency (%)
지 1
33.3%
산 1
33.3%
동 1
33.3%

Unnamed: 14
Text

MISSING 

Distinct21
Distinct (%)63.6%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T10:09:47.573508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length2
Min length1

Characters and Unicode

Total characters66
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

Unique17 ?
Unique (%)51.5%

Sample

1st row지산2동
2nd row2,381
3rd row4,368
4th row9
5th row6
ValueCountFrequency (%)
0 10
30.3%
9 2
 
6.1%
6 2
 
6.1%
2,381 2
 
6.1%
39 1
 
3.0%
88 1
 
3.0%
18 1
 
3.0%
2 1
 
3.0%
29 1
 
3.0%
31 1
 
3.0%
Other values (11) 11
33.3%
2024-02-10T10:09:48.373588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 12
18.2%
2 9
13.6%
3 7
10.6%
8 7
10.6%
1 5
7.6%
9 5
7.6%
6 5
7.6%
, 4
 
6.1%
4 4
 
6.1%
7 2
 
3.0%
Other values (5) 6
9.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 58
87.9%
Other Punctuation 4
 
6.1%
Other Letter 3
 
4.5%
Dash Punctuation 1
 
1.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 12
20.7%
2 9
15.5%
3 7
12.1%
8 7
12.1%
1 5
8.6%
9 5
8.6%
6 5
8.6%
4 4
 
6.9%
7 2
 
3.4%
5 2
 
3.4%
Other Letter
ValueCountFrequency (%)
지 1
33.3%
산 1
33.3%
동 1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 63
95.5%
Hangul 3
 
4.5%

Most frequent character per script

Common
ValueCountFrequency (%)
0 12
19.0%
2 9
14.3%
3 7
11.1%
8 7
11.1%
1 5
7.9%
9 5
7.9%
6 5
7.9%
, 4
 
6.3%
4 4
 
6.3%
7 2
 
3.2%
Other values (2) 3
 
4.8%
Hangul
ValueCountFrequency (%)
지 1
33.3%
산 1
33.3%
동 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 63
95.5%
Hangul 3
 
4.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 12
19.0%
2 9
14.3%
3 7
11.1%
8 7
11.1%
1 5
7.9%
9 5
7.9%
6 5
7.9%
, 4
 
6.3%
4 4
 
6.3%
7 2
 
3.2%
Other values (2) 3
 
4.8%
Hangul
ValueCountFrequency (%)
지 1
33.3%
산 1
33.3%
동 1
33.3%

Unnamed: 15
Text

MISSING 

Distinct22
Distinct (%)66.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T10:09:48.701603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
Mean length2.030303
Min length1

Characters and Unicode

Total characters67
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 row서남동
2nd row2,241
3rd row2,969
4th row54
5th row3
ValueCountFrequency (%)
0 7
21.2%
3 2
 
6.1%
41 2
 
6.1%
42 2
 
6.1%
1 2
 
6.1%
54 2
 
6.1%
43 1
 
3.0%
48 1
 
3.0%
2,243 1
 
3.0%
10 1
 
3.0%
Other values (12) 12
36.4%
2024-02-10T10:09:49.485599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 13
19.4%
4 11
16.4%
0 8
11.9%
1 7
10.4%
3 6
9.0%
9 5
 
7.5%
5 4
 
6.0%
, 4
 
6.0%
8 3
 
4.5%
6 1
 
1.5%
Other values (5) 5
 
7.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 59
88.1%
Other Punctuation 4
 
6.0%
Other Letter 3
 
4.5%
Dash Punctuation 1
 
1.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 13
22.0%
4 11
18.6%
0 8
13.6%
1 7
11.9%
3 6
10.2%
9 5
 
8.5%
5 4
 
6.8%
8 3
 
5.1%
6 1
 
1.7%
7 1
 
1.7%
Other Letter
ValueCountFrequency (%)
서 1
33.3%
남 1
33.3%
동 1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
2 13
20.3%
4 11
17.2%
0 8
12.5%
1 7
10.9%
3 6
9.4%
9 5
 
7.8%
5 4
 
6.2%
, 4
 
6.2%
8 3
 
4.7%
6 1
 
1.6%
Other values (2) 2
 
3.1%
Hangul
ValueCountFrequency (%)
서 1
33.3%
남 1
33.3%
동 1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 13
20.3%
4 11
17.2%
0 8
12.5%
1 7
10.9%
3 6
9.4%
9 5
 
7.8%
5 4
 
6.2%
, 4
 
6.2%
8 3
 
4.7%
6 1
 
1.6%
Other values (2) 2
 
3.1%
Hangul
ValueCountFrequency (%)
서 1
33.3%
남 1
33.3%
동 1
33.3%

Unnamed: 16
Text

MISSING 

Distinct23
Distinct (%)69.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T10:09:49.810311image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length2
Mean length2
Min length1

Characters and Unicode

Total characters66
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

Unique18 ?
Unique (%)54.5%

Sample

1st row학동
2nd row3,524
3rd row7,394
4th row80
5th row9
ValueCountFrequency (%)
0 7
21.2%
41 2
 
6.1%
17 2
 
6.1%
9 2
 
6.1%
5 2
 
6.1%
33 1
 
3.0%
97 1
 
3.0%
50 1
 
3.0%
7,411 1
 
3.0%
3,529 1
 
3.0%
Other values (13) 13
39.4%
2024-02-10T10:09:50.667857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 9
13.6%
1 9
13.6%
7 8
12.1%
4 7
10.6%
9 7
10.6%
3 7
10.6%
5 5
7.6%
, 4
6.1%
8 3
 
4.5%
2 3
 
4.5%
Other values (4) 4
6.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 59
89.4%
Other Punctuation 4
 
6.1%
Other Letter 2
 
3.0%
Dash Punctuation 1
 
1.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 9
15.3%
1 9
15.3%
7 8
13.6%
4 7
11.9%
9 7
11.9%
3 7
11.9%
5 5
8.5%
8 3
 
5.1%
2 3
 
5.1%
6 1
 
1.7%
Other Letter
ValueCountFrequency (%)
학 1
50.0%
동 1
50.0%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 64
97.0%
Hangul 2
 
3.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 9
14.1%
1 9
14.1%
7 8
12.5%
4 7
10.9%
9 7
10.9%
3 7
10.9%
5 5
7.8%
, 4
6.2%
8 3
 
4.7%
2 3
 
4.7%
Other values (2) 2
 
3.1%
Hangul
ValueCountFrequency (%)
학 1
50.0%
동 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 64
97.0%
Hangul 2
 
3.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 9
14.1%
1 9
14.1%
7 8
12.5%
4 7
10.9%
9 7
10.9%
3 7
10.9%
5 5
7.8%
, 4
6.2%
8 3
 
4.7%
2 3
 
4.7%
Other values (2) 2
 
3.1%
Hangul
ValueCountFrequency (%)
학 1
50.0%
동 1
50.0%

Unnamed: 17
Text

MISSING 

Distinct23
Distinct (%)69.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T10:09:51.067008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length2
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

Unique20 ?
Unique (%)60.6%

Sample

1st row학운동
2nd row5,214
3rd row11,200
4th row45
5th row20
ValueCountFrequency (%)
0 8
24.2%
45 3
 
9.1%
34 2
 
6.1%
1 1
 
3.0%
58 1
 
3.0%
11,176 1
 
3.0%
5,208 1
 
3.0%
24 1
 
3.0%
6 1
 
3.0%
11 1
 
3.0%
Other values (13) 13
39.4%
2024-02-10T10:09:51.754400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 14
18.9%
0 13
17.6%
4 12
16.2%
5 7
9.5%
2 7
9.5%
, 4
 
5.4%
6 4
 
5.4%
7 3
 
4.1%
3 2
 
2.7%
- 2
 
2.7%
Other values (5) 6
8.1%

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 14
21.5%
0 13
20.0%
4 12
18.5%
5 7
10.8%
2 7
10.8%
6 4
 
6.2%
7 3
 
4.6%
3 2
 
3.1%
8 2
 
3.1%
9 1
 
1.5%
Other Letter
ValueCountFrequency (%)
학 1
33.3%
운 1
33.3%
동 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 14
19.7%
0 13
18.3%
4 12
16.9%
5 7
9.9%
2 7
9.9%
, 4
 
5.6%
6 4
 
5.6%
7 3
 
4.2%
3 2
 
2.8%
- 2
 
2.8%
Other values (2) 3
 
4.2%
Hangul
ValueCountFrequency (%)
학 1
33.3%
운 1
33.3%
동 1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 14
19.7%
0 13
18.3%
4 12
16.9%
5 7
9.9%
2 7
9.9%
, 4
 
5.6%
6 4
 
5.6%
7 3
 
4.2%
3 2
 
2.8%
- 2
 
2.8%
Other values (2) 3
 
4.2%
Hangul
ValueCountFrequency (%)
학 1
33.3%
운 1
33.3%
동 1
33.3%

Unnamed: 18
Text

MISSING 

Distinct20
Distinct (%)60.6%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T10:09:52.098719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length2.0909091
Min length1

Characters and Unicode

Total characters69
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 row지원1동
2nd row4,203
3rd row9,024
4th row21
5th row8
ValueCountFrequency (%)
0 8
24.2%
8 4
 
12.1%
21 2
 
6.1%
51 2
 
6.1%
40 2
 
6.1%
28 1
 
3.0%
57 1
 
3.0%
4,211 1
 
3.0%
4 1
 
3.0%
5 1
 
3.0%
Other values (10) 10
30.3%
2024-02-10T10:09:52.876707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 16
23.2%
2 10
14.5%
1 10
14.5%
4 7
10.1%
8 5
 
7.2%
5 5
 
7.2%
9 4
 
5.8%
, 4
 
5.8%
3 3
 
4.3%
지 1
 
1.4%
Other values (4) 4
 
5.8%

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 16
26.2%
2 10
16.4%
1 10
16.4%
4 7
11.5%
8 5
 
8.2%
5 5
 
8.2%
9 4
 
6.6%
3 3
 
4.9%
7 1
 
1.6%
Other Letter
ValueCountFrequency (%)
지 1
33.3%
원 1
33.3%
동 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 16
24.2%
2 10
15.2%
1 10
15.2%
4 7
10.6%
8 5
 
7.6%
5 5
 
7.6%
9 4
 
6.1%
, 4
 
6.1%
3 3
 
4.5%
- 1
 
1.5%
Hangul
ValueCountFrequency (%)
지 1
33.3%
원 1
33.3%
동 1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 16
24.2%
2 10
15.2%
1 10
15.2%
4 7
10.6%
8 5
 
7.6%
5 5
 
7.6%
9 4
 
6.1%
, 4
 
6.1%
3 3
 
4.5%
- 1
 
1.5%
Hangul
ValueCountFrequency (%)
지 1
33.3%
원 1
33.3%
동 1
33.3%

Unnamed: 19
Text

MISSING 

Distinct25
Distinct (%)75.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T10:09:53.218593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.5151515
Min length1

Characters and Unicode

Total characters83
Distinct characters14
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique22 ?
Unique (%)66.7%

Sample

1st row지원2동
2nd row7,395
3rd row16,252
4th row108
5th row7
ValueCountFrequency (%)
0 7
21.2%
9 2
 
6.1%
7 2
 
6.1%
116 1
 
3.0%
108 1
 
3.0%
16,252 1
 
3.0%
16,481 1
 
3.0%
7,544 1
 
3.0%
1 1
 
3.0%
229 1
 
3.0%
Other values (15) 15
45.5%
2024-02-10T10:09:53.951782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 15
18.1%
0 13
15.7%
2 10
12.0%
9 8
9.6%
4 8
9.6%
8 7
8.4%
7 6
 
7.2%
6 4
 
4.8%
5 4
 
4.8%
, 4
 
4.8%
Other values (4) 4
 
4.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 76
91.6%
Other Punctuation 4
 
4.8%
Other Letter 3
 
3.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 15
19.7%
0 13
17.1%
2 10
13.2%
9 8
10.5%
4 8
10.5%
8 7
9.2%
7 6
 
7.9%
6 4
 
5.3%
5 4
 
5.3%
3 1
 
1.3%
Other Letter
ValueCountFrequency (%)
지 1
33.3%
원 1
33.3%
동 1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
1 15
18.8%
0 13
16.2%
2 10
12.5%
9 8
10.0%
4 8
10.0%
8 7
8.8%
7 6
 
7.5%
6 4
 
5.0%
5 4
 
5.0%
, 4
 
5.0%
Hangul
ValueCountFrequency (%)
지 1
33.3%
원 1
33.3%
동 1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 15
18.8%
0 13
16.2%
2 10
12.5%
9 8
10.0%
4 8
10.0%
8 7
8.8%
7 6
 
7.5%
6 4
 
5.0%
5 4
 
5.0%
, 4
 
5.0%
Hangul
ValueCountFrequency (%)
지 1
33.3%
원 1
33.3%
동 1
33.3%

Correlations

2024-02-10T10:09:54.251057image/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: 20.0001.000NaNNaN1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
Unnamed: 31.000NaN1.000NaN1.0001.0000.5831.0001.0001.0000.8650.7901.0000.5831.0001.0000.7901.000
Unnamed: 4NaNNaNNaN1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
Unnamed: 51.0001.0001.0001.0001.0000.9920.9920.9930.9930.9910.9910.9930.9910.9910.9940.9920.9890.994
Unnamed: 61.0001.0001.0001.0000.9921.0000.9700.9810.9750.9870.9620.9660.9490.9550.9910.9860.9720.985
Unnamed: 71.0001.0000.5831.0000.9920.9701.0000.9790.9950.9730.9790.9760.9830.9890.9740.9810.9870.992
Unnamed: 81.0001.0001.0001.0000.9930.9810.9791.0000.9980.9920.9870.9920.9910.9870.9890.9870.9920.996
Unnamed: 91.0001.0001.0001.0000.9930.9750.9950.9981.0001.0001.0001.0001.0000.9970.9870.9951.0000.995
Unnamed: 101.0001.0001.0001.0000.9910.9870.9730.9921.0001.0000.9870.9910.9870.9960.9810.9870.9850.993
Unnamed: 111.0001.0000.8651.0000.9910.9620.9790.9871.0000.9871.0000.9950.9940.9930.9850.9910.9810.992
Unnamed: 131.0001.0000.7901.0000.9930.9660.9760.9921.0000.9910.9951.0000.9960.9850.9790.9880.9870.995
Unnamed: 141.0001.0001.0001.0000.9910.9490.9830.9911.0000.9870.9940.9961.0000.9870.9780.9850.9900.996
Unnamed: 151.0001.0000.5831.0000.9910.9550.9890.9870.9970.9960.9930.9850.9871.0000.9710.9850.9900.991
Unnamed: 161.0001.0001.0001.0000.9940.9910.9740.9890.9870.9810.9850.9790.9780.9711.0000.9880.9780.996
Unnamed: 171.0001.0001.0001.0000.9920.9860.9810.9870.9950.9870.9910.9880.9850.9850.9881.0000.9870.985
Unnamed: 181.0001.0000.7901.0000.9890.9720.9870.9921.0000.9850.9810.9870.9900.9900.9780.9871.0000.996
Unnamed: 191.0001.0001.0001.0000.9940.9850.9920.9960.9950.9930.9920.9950.9960.9910.9960.9850.9961.000

Missing values

2024-02-10T10:09:30.098644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-02-10T10:09:31.096755image/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.
2024-02-10T10:09:32.247403image/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>2023.04.03<NA><NA><NA><NA><NA><NA><NA>
1<NA>작성기준 :<NA>2023.03 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>54,3424,0872,4405,8125,4774,4044,729<NA>2,4352,3812,2413,5245,2144,2037,395
4<NA>전월말인구수<NA><NA><NA>106,1015,2133,73310,56813,0438,19110,017<NA>4,1294,3682,9697,39411,2009,02416,252
5<NA>전월말거주불명자수<NA><NA><NA>7073811576286329<NA>41954804521108
6<NA>전월말재외국민등록자수<NA><NA><NA>10778121266<NA>36392087
7<NA>증 가 요 인전 입계<NA>1,7601436717318911487<NA>9572839791102447
8<NA><NA><NA>남자<NA>875733197965342<NA>514541504651199
9<NA><NA><NA>여자<NA>885703676936145<NA>442742474551248
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>1000000<NA>0010000
26<NA><NA>국외<NA><NA>0000000<NA>0000000
27<NA><NA>기타<NA><NA>0000000<NA>0000000
28<NA>세대수증감<NA><NA><NA>16514711-21-11-4<NA>11025-68149
29<NA>인구수증감<NA><NA><NA>1460-913-640-5<NA>21-18-1017-24-4229
30<NA>거주불명자수증감<NA><NA><NA>-2-101000<NA>000-3001
31<NA>금월말세대수<NA><NA><NA>54,5074,1012,4475,8235,4564,3934,725<NA>2,4462,3812,2433,5295,2084,2117,544
32<NA>금월말인구수<NA><NA><NA>106,2475,2133,72410,58112,9798,19110,012<NA>4,1504,3502,9597,41111,1769,02016,481
33<NA>금월말거주불명자수<NA><NA><NA>7053711577286329<NA>41954774521109
34<NA>금월말재외국민등록자수<NA><NA><NA>10667121266<NA>36392187

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>국외<NA><NA>0000000<NA>00000002
1<NA>기타<NA><NA>0000000<NA>00000002