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

Description2023-09-14
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 10:11:16.260099
Analysis finished2024-02-10 10:11:22.326449
Duration6.07 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
2024-02-10T10:11:22.627048image/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%
2024-02-10T10:11:23.898438image/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
2024-02-10T10:11:24.273912image/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%
2024-02-10T10:11:25.252893image/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
2024-02-10T10:11:25.707365image/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 row2023.06 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%
2023.06 1
7.1%
현재 1
7.1%
2024-02-10T10:11:26.533614image/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%
여 2
 
4.9%
내 2
 
4.9%
간 2
 
4.9%
광 2
 
4.9%
남 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 (%)
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 (%)
2 2
33.3%
0 2
33.3%
3 1
16.7%
6 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 (%)
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%
2 2
20.0%
0 2
20.0%
3 1
 
10.0%
6 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 (%)
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%
2 2
20.0%
0 2
20.0%
3 1
 
10.0%
6 1
 
10.0%
. 1
 
10.0%

Unnamed: 4
Text

MISSING 

Distinct2
Distinct (%)50.0%
Missing31
Missing (%)88.6%
Memory size412.0 B
2024-02-10T10:11:26.867632image/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%
2024-02-10T10:11:27.829710image/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 

Distinct28
Distinct (%)84.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T10:11:28.304223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length2.969697
Min length1

Characters and Unicode

Total characters98
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

Unique25 ?
Unique (%)75.8%

Sample

1st row합 계
2nd row54,805
3rd row106,595
4th row709
5th row108
ValueCountFrequency (%)
0 4
 
11.8%
249 2
 
5.9%
108 2
 
5.9%
555 1
 
2.9%
1,111 1
 
2.9%
106,666 1
 
2.9%
54,882 1
 
2.9%
7 1
 
2.9%
71 1
 
2.9%
77 1
 
2.9%
Other values (19) 19
55.9%
2024-02-10T10:11:29.236166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 14
14.3%
1 13
13.3%
0 12
12.2%
6 12
12.2%
7 9
9.2%
8 8
8.2%
2 7
7.1%
4 6
6.1%
, 6
6.1%
9 5
 
5.1%
Other values (4) 6
6.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 88
89.8%
Other Punctuation 6
 
6.1%
Space Separator 2
 
2.0%
Other Letter 2
 
2.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 14
15.9%
1 13
14.8%
0 12
13.6%
6 12
13.6%
7 9
10.2%
8 8
9.1%
2 7
8.0%
4 6
6.8%
9 5
 
5.7%
3 2
 
2.3%
Other Letter
ValueCountFrequency (%)
합 1
50.0%
계 1
50.0%
Other Punctuation
ValueCountFrequency (%)
, 6
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 96
98.0%
Hangul 2
 
2.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 14
14.6%
1 13
13.5%
0 12
12.5%
6 12
12.5%
7 9
9.4%
8 8
8.3%
2 7
7.3%
4 6
6.2%
, 6
6.2%
9 5
 
5.2%
Other values (2) 4
 
4.2%
Hangul
ValueCountFrequency (%)
합 1
50.0%
계 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 96
98.0%
Hangul 2
 
2.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 14
14.6%
1 13
13.5%
0 12
12.5%
6 12
12.5%
7 9
9.4%
8 8
8.3%
2 7
7.3%
4 6
6.2%
, 6
6.2%
9 5
 
5.2%
Other values (2) 4
 
4.2%
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
2024-02-10T10:11:29.718892image/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

Unique19 ?
Unique (%)57.6%

Sample

1st row충장동
2nd row4,180
3rd row5,316
4th row37
5th row6
ValueCountFrequency (%)
0 8
24.2%
6 2
 
6.1%
67 2
 
6.1%
37 2
 
6.1%
13 1
 
3.0%
54 1
 
3.0%
4,203 1
 
3.0%
26 1
 
3.0%
23 1
 
3.0%
5 1
 
3.0%
Other values (13) 13
39.4%
2024-02-10T10:11:30.656049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

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

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 11
18.3%
3 8
13.3%
5 8
13.3%
4 7
11.7%
6 6
10.0%
1 6
10.0%
2 5
8.3%
7 4
 
6.7%
8 4
 
6.7%
9 1
 
1.7%
Other Letter
ValueCountFrequency (%)
충 1
33.3%
장 1
33.3%
동 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 11
17.2%
3 8
12.5%
5 8
12.5%
4 7
10.9%
6 6
9.4%
1 6
9.4%
2 5
7.8%
7 4
 
6.2%
, 4
 
6.2%
8 4
 
6.2%
Hangul
ValueCountFrequency (%)
충 1
33.3%
장 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 (%)
0 11
17.2%
3 8
12.5%
5 8
12.5%
4 7
10.9%
6 6
9.4%
1 6
9.4%
2 5
7.8%
7 4
 
6.2%
, 4
 
6.2%
8 4
 
6.2%
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
2024-02-10T10:11:30.999846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
Mean length2
Min length1

Characters and Unicode

Total characters66
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

Unique14 ?
Unique (%)42.4%

Sample

1st row동명동
2nd row2,441
3rd row3,716
4th row118
5th row7
ValueCountFrequency (%)
0 10
30.3%
22 3
 
9.1%
7 2
 
6.1%
8 2
 
6.1%
118 2
 
6.1%
3,716 1
 
3.0%
59 1
 
3.0%
34 1
 
3.0%
25 1
 
3.0%
19 1
 
3.0%
Other values (9) 9
27.3%
2024-02-10T10:11:31.806595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 12
18.2%
0 11
16.7%
1 9
13.6%
4 6
9.1%
8 5
7.6%
9 5
7.6%
7 4
 
6.1%
, 4
 
6.1%
5 3
 
4.5%
3 3
 
4.5%
Other values (3) 4
 
6.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 59
89.4%
Other Punctuation 4
 
6.1%
Other Letter 3
 
4.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 12
20.3%
0 11
18.6%
1 9
15.3%
4 6
10.2%
8 5
8.5%
9 5
8.5%
7 4
 
6.8%
5 3
 
5.1%
3 3
 
5.1%
6 1
 
1.7%
Other Letter
ValueCountFrequency (%)
동 2
66.7%
명 1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
2 12
19.0%
0 11
17.5%
1 9
14.3%
4 6
9.5%
8 5
7.9%
9 5
7.9%
7 4
 
6.3%
, 4
 
6.3%
5 3
 
4.8%
3 3
 
4.8%
Hangul
ValueCountFrequency (%)
동 2
66.7%
명 1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 12
19.0%
0 11
17.5%
1 9
14.3%
4 6
9.5%
8 5
7.9%
9 5
7.9%
7 4
 
6.3%
, 4
 
6.3%
5 3
 
4.8%
3 3
 
4.8%
Hangul
ValueCountFrequency (%)
동 2
66.7%
명 1
33.3%

Unnamed: 8
Text

MISSING 

Distinct25
Distinct (%)75.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T10:11:32.167348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
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

Unique22 ?
Unique (%)66.7%

Sample

1st row계림1동
2nd row5,811
3rd row10,561
4th row77
5th row12
ValueCountFrequency (%)
0 7
21.2%
12 3
 
9.1%
58 2
 
6.1%
25 1
 
3.0%
116 1
 
3.0%
10,549 1
 
3.0%
5,801 1
 
3.0%
3 1
 
3.0%
10 1
 
3.0%
7 1
 
3.0%
Other values (14) 14
42.4%
2024-02-10T10:11:33.045789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 17
22.1%
0 14
18.2%
5 12
15.6%
2 6
 
7.8%
8 5
 
6.5%
, 4
 
5.2%
7 4
 
5.2%
6 3
 
3.9%
4 3
 
3.9%
3 3
 
3.9%
Other values (5) 6
 
7.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 68
88.3%
Other Punctuation 4
 
5.2%
Other Letter 3
 
3.9%
Dash Punctuation 2
 
2.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 17
25.0%
0 14
20.6%
5 12
17.6%
2 6
 
8.8%
8 5
 
7.4%
7 4
 
5.9%
6 3
 
4.4%
4 3
 
4.4%
3 3
 
4.4%
9 1
 
1.5%
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 74
96.1%
Hangul 3
 
3.9%

Most frequent character per script

Common
ValueCountFrequency (%)
1 17
23.0%
0 14
18.9%
5 12
16.2%
2 6
 
8.1%
8 5
 
6.8%
, 4
 
5.4%
7 4
 
5.4%
6 3
 
4.1%
4 3
 
4.1%
3 3
 
4.1%
Other values (2) 3
 
4.1%
Hangul
ValueCountFrequency (%)
계 1
33.3%
림 1
33.3%
동 1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 17
23.0%
0 14
18.9%
5 12
16.2%
2 6
 
8.1%
8 5
 
6.8%
, 4
 
5.4%
7 4
 
5.4%
6 3
 
4.1%
4 3
 
4.1%
3 3
 
4.1%
Other values (2) 3
 
4.1%
Hangul
ValueCountFrequency (%)
계 1
33.3%
림 1
33.3%
동 1
33.3%

Unnamed: 9
Text

MISSING 

Distinct25
Distinct (%)75.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T10:11:33.415807image/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

Unique22 ?
Unique (%)66.7%

Sample

1st row계림2동
2nd row5,527
3rd row13,093
4th row27
5th row12
ValueCountFrequency (%)
0 7
21.2%
12 2
 
6.1%
27 2
 
6.1%
14 1
 
3.0%
127 1
 
3.0%
5,550 1
 
3.0%
49 1
 
3.0%
23 1
 
3.0%
8 1
 
3.0%
28 1
 
3.0%
Other values (15) 15
45.5%
2024-02-10T10:11:34.266958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 12
15.8%
0 11
14.5%
1 10
13.2%
3 8
10.5%
5 7
9.2%
4 5
6.6%
7 4
 
5.3%
, 4
 
5.3%
9 4
 
5.3%
6 4
 
5.3%
Other values (4) 7
9.2%

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 (%)
2 12
17.4%
0 11
15.9%
1 10
14.5%
3 8
11.6%
5 7
10.1%
4 5
7.2%
7 4
 
5.8%
9 4
 
5.8%
6 4
 
5.8%
8 4
 
5.8%
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 73
96.1%
Hangul 3
 
3.9%

Most frequent character per script

Common
ValueCountFrequency (%)
2 12
16.4%
0 11
15.1%
1 10
13.7%
3 8
11.0%
5 7
9.6%
4 5
6.8%
7 4
 
5.5%
, 4
 
5.5%
9 4
 
5.5%
6 4
 
5.5%
Hangul
ValueCountFrequency (%)
계 1
33.3%
림 1
33.3%
동 1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 12
16.4%
0 11
15.1%
1 10
13.7%
3 8
11.0%
5 7
9.6%
4 5
6.8%
7 4
 
5.5%
, 4
 
5.5%
9 4
 
5.5%
6 4
 
5.5%
Hangul
ValueCountFrequency (%)
계 1
33.3%
림 1
33.3%
동 1
33.3%

Unnamed: 10
Text

MISSING 

Distinct25
Distinct (%)73.5%
Missing1
Missing (%)2.9%
Memory size412.0 B
2024-02-10T10:11:34.663687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.2058824
Min length1

Characters and Unicode

Total characters75
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

Unique22 ?
Unique (%)64.7%

Sample

1st row출력일자 :
2nd row산수1동
3rd row4,383
4th row8,165
5th row62
ValueCountFrequency (%)
0 7
20.0%
1 3
 
8.6%
6 2
 
5.7%
1
 
2.9%
8,150 1
 
2.9%
4,384 1
 
2.9%
15 1
 
2.9%
5 1
 
2.9%
29 1
 
2.9%
40 1
 
2.9%
Other values (16) 16
45.7%
2024-02-10T10:11:35.494754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 10
13.3%
4 9
12.0%
1 9
12.0%
3 8
10.7%
5 7
9.3%
8 6
8.0%
6 5
6.7%
, 4
 
5.3%
2 3
 
4.0%
9 2
 
2.7%
Other values (11) 12
16.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 61
81.3%
Other Letter 7
 
9.3%
Other Punctuation 5
 
6.7%
Space Separator 1
 
1.3%
Dash Punctuation 1
 
1.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 10
16.4%
4 9
14.8%
1 9
14.8%
3 8
13.1%
5 7
11.5%
8 6
9.8%
6 5
8.2%
2 3
 
4.9%
9 2
 
3.3%
7 2
 
3.3%
Other Letter
ValueCountFrequency (%)
동 1
14.3%
수 1
14.3%
산 1
14.3%
출 1
14.3%
력 1
14.3%
일 1
14.3%
자 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 68
90.7%
Hangul 7
 
9.3%

Most frequent character per script

Common
ValueCountFrequency (%)
0 10
14.7%
4 9
13.2%
1 9
13.2%
3 8
11.8%
5 7
10.3%
8 6
8.8%
6 5
7.4%
, 4
 
5.9%
2 3
 
4.4%
9 2
 
2.9%
Other values (4) 5
7.4%
Hangul
ValueCountFrequency (%)
동 1
14.3%
수 1
14.3%
산 1
14.3%
출 1
14.3%
력 1
14.3%
일 1
14.3%
자 1
14.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 68
90.7%
Hangul 7
 
9.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 10
14.7%
4 9
13.2%
1 9
13.2%
3 8
11.8%
5 7
10.3%
8 6
8.8%
6 5
7.4%
, 4
 
5.9%
2 3
 
4.4%
9 2
 
2.9%
Other values (4) 5
7.4%
Hangul
ValueCountFrequency (%)
동 1
14.3%
수 1
14.3%
산 1
14.3%
출 1
14.3%
력 1
14.3%
일 1
14.3%
자 1
14.3%

Unnamed: 11
Text

MISSING 

Distinct23
Distinct (%)69.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T10:11:35.934178image/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

Unique20 ?
Unique (%)60.6%

Sample

1st row산수2동
2nd row4,714
3rd row9,957
4th row26
5th row6
ValueCountFrequency (%)
0 8
24.2%
6 3
 
9.1%
26 3
 
9.1%
43 1
 
3.0%
9,957 1
 
3.0%
4,714 1
 
3.0%
4,708 1
 
3.0%
20 1
 
3.0%
5 1
 
3.0%
28 1
 
3.0%
Other values (12) 12
36.4%
2024-02-10T10:11:36.902097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 11
15.9%
6 8
11.6%
2 7
10.1%
3 7
10.1%
4 6
8.7%
8 5
7.2%
1 5
7.2%
7 5
7.2%
, 4
 
5.8%
9 4
 
5.8%
Other values (5) 7
10.1%

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%
6 8
13.3%
2 7
11.7%
3 7
11.7%
4 6
10.0%
8 5
8.3%
1 5
8.3%
7 5
8.3%
9 4
 
6.7%
5 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 66
95.7%
Hangul 3
 
4.3%

Most frequent character per script

Common
ValueCountFrequency (%)
0 11
16.7%
6 8
12.1%
2 7
10.6%
3 7
10.6%
4 6
9.1%
8 5
7.6%
1 5
7.6%
7 5
7.6%
, 4
 
6.1%
9 4
 
6.1%
Other values (2) 4
 
6.1%
Hangul
ValueCountFrequency (%)
산 1
33.3%
수 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%
6 8
12.1%
2 7
10.6%
3 7
10.6%
4 6
9.1%
8 5
7.6%
1 5
7.6%
7 5
7.6%
, 4
 
6.1%
9 4
 
6.1%
Other values (2) 4
 
6.1%
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
Minimum2023-08-30 00:00:00
Maximum2023-08-30 00:00:00
2024-02-10T10:11:37.420678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-10T10:11:37.752293image/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
2024-02-10T10:11:38.041925image/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 row2,426
3rd row4,122
4th row42
5th row3
ValueCountFrequency (%)
0 9
27.3%
42 2
 
6.1%
3 2
 
6.1%
22 2
 
6.1%
21 2
 
6.1%
27 1
 
3.0%
46 1
 
3.0%
2,447 1
 
3.0%
5 1
 
3.0%
20 1
 
3.0%
Other values (11) 11
33.3%
2024-02-10T10:11:39.105290image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 20
29.4%
4 12
17.6%
0 10
14.7%
1 7
 
10.3%
3 5
 
7.4%
, 4
 
5.9%
7 3
 
4.4%
6 2
 
2.9%
지 1
 
1.5%
산 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 (%)
2 20
32.8%
4 12
19.7%
0 10
16.4%
1 7
 
11.5%
3 5
 
8.2%
7 3
 
4.9%
6 2
 
3.3%
9 1
 
1.6%
5 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 (%)
2 20
30.8%
4 12
18.5%
0 10
15.4%
1 7
 
10.8%
3 5
 
7.7%
, 4
 
6.2%
7 3
 
4.6%
6 2
 
3.1%
9 1
 
1.5%
5 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 (%)
2 20
30.8%
4 12
18.5%
0 10
15.4%
1 7
 
10.8%
3 5
 
7.7%
, 4
 
6.2%
7 3
 
4.6%
6 2
 
3.1%
9 1
 
1.5%
5 1
 
1.5%
Hangul
ValueCountFrequency (%)
지 1
33.3%
산 1
33.3%
동 1
33.3%

Unnamed: 14
Text

MISSING 

Distinct23
Distinct (%)69.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T10:11:39.435046image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length1.969697
Min length1

Characters and Unicode

Total characters65
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 row지산2동
2nd row2,383
3rd row4,340
4th row9
5th row7
ValueCountFrequency (%)
0 9
27.3%
5 2
 
6.1%
9 2
 
6.1%
7 2
 
6.1%
4,340 1
 
3.0%
2,383 1
 
3.0%
2,380 1
 
3.0%
3 1
 
3.0%
4 1
 
3.0%
19 1
 
3.0%
Other values (12) 12
36.4%
2024-02-10T10:11:40.288578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 13
20.0%
3 8
12.3%
2 7
10.8%
4 6
9.2%
1 6
9.2%
5 5
 
7.7%
, 4
 
6.2%
9 3
 
4.6%
6 3
 
4.6%
8 3
 
4.6%
Other values (5) 7
10.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 56
86.2%
Other Punctuation 4
 
6.2%
Other Letter 3
 
4.6%
Dash Punctuation 2
 
3.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 13
23.2%
3 8
14.3%
2 7
12.5%
4 6
10.7%
1 6
10.7%
5 5
 
8.9%
9 3
 
5.4%
6 3
 
5.4%
8 3
 
5.4%
7 2
 
3.6%
Other Letter
ValueCountFrequency (%)
지 1
33.3%
산 1
33.3%
동 1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 62
95.4%
Hangul 3
 
4.6%

Most frequent character per script

Common
ValueCountFrequency (%)
0 13
21.0%
3 8
12.9%
2 7
11.3%
4 6
9.7%
1 6
9.7%
5 5
 
8.1%
, 4
 
6.5%
9 3
 
4.8%
6 3
 
4.8%
8 3
 
4.8%
Other values (2) 4
 
6.5%
Hangul
ValueCountFrequency (%)
지 1
33.3%
산 1
33.3%
동 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 62
95.4%
Hangul 3
 
4.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 13
21.0%
3 8
12.9%
2 7
11.3%
4 6
9.7%
1 6
9.7%
5 5
 
8.1%
, 4
 
6.5%
9 3
 
4.8%
6 3
 
4.8%
8 3
 
4.8%
Other values (2) 4
 
6.5%
Hangul
ValueCountFrequency (%)
지 1
33.3%
산 1
33.3%
동 1
33.3%

Unnamed: 15
Text

MISSING 

Distinct21
Distinct (%)63.6%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T10:11:40.765624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
Mean length2.030303
Min length1

Characters and Unicode

Total characters67
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

Unique14 ?
Unique (%)42.4%

Sample

1st row서남동
2nd row2,255
3rd row2,956
4th row54
5th row3
ValueCountFrequency (%)
0 6
18.2%
32 3
 
9.1%
10 2
 
6.1%
1 2
 
6.1%
2 2
 
6.1%
3 2
 
6.1%
54 2
 
6.1%
13 1
 
3.0%
65 1
 
3.0%
33 1
 
3.0%
Other values (11) 11
33.3%
2024-02-10T10:11:41.863580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 16
23.9%
5 9
13.4%
0 8
11.9%
3 8
11.9%
1 8
11.9%
6 5
 
7.5%
, 4
 
6.0%
4 3
 
4.5%
9 2
 
3.0%
7 1
 
1.5%
Other values (3) 3
 
4.5%

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 (%)
2 16
26.7%
5 9
15.0%
0 8
13.3%
3 8
13.3%
1 8
13.3%
6 5
 
8.3%
4 3
 
5.0%
9 2
 
3.3%
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%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
2 16
25.0%
5 9
14.1%
0 8
12.5%
3 8
12.5%
1 8
12.5%
6 5
 
7.8%
, 4
 
6.2%
4 3
 
4.7%
9 2
 
3.1%
7 1
 
1.6%
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 16
25.0%
5 9
14.1%
0 8
12.5%
3 8
12.5%
1 8
12.5%
6 5
 
7.8%
, 4
 
6.2%
4 3
 
4.7%
9 2
 
3.1%
7 1
 
1.6%
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
2024-02-10T10:11:42.264241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
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 row3,532
3rd row7,404
4th row83
5th row9
ValueCountFrequency (%)
0 7
21.2%
9 2
 
6.1%
1 2
 
6.1%
31 2
 
6.1%
83 2
 
6.1%
4 1
 
3.0%
35 1
 
3.0%
3,533 1
 
3.0%
11 1
 
3.0%
7 1
 
3.0%
Other values (13) 13
39.4%
2024-02-10T10:11:43.242707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 16
24.2%
1 10
15.2%
0 9
13.6%
9 6
 
9.1%
, 4
 
6.1%
4 4
 
6.1%
8 3
 
4.5%
5 3
 
4.5%
2 3
 
4.5%
7 3
 
4.5%
Other values (4) 5
 
7.6%

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 (%)
3 16
27.1%
1 10
16.9%
0 9
15.3%
9 6
 
10.2%
4 4
 
6.8%
8 3
 
5.1%
5 3
 
5.1%
2 3
 
5.1%
7 3
 
5.1%
6 2
 
3.4%
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 (%)
3 16
25.0%
1 10
15.6%
0 9
14.1%
9 6
 
9.4%
, 4
 
6.2%
4 4
 
6.2%
8 3
 
4.7%
5 3
 
4.7%
2 3
 
4.7%
7 3
 
4.7%
Other values (2) 3
 
4.7%
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 (%)
3 16
25.0%
1 10
15.6%
0 9
14.1%
9 6
 
9.4%
, 4
 
6.2%
4 4
 
6.2%
8 3
 
4.7%
5 3
 
4.7%
2 3
 
4.7%
7 3
 
4.7%
Other values (2) 3
 
4.7%
Hangul
ValueCountFrequency (%)
학 1
50.0%
동 1
50.0%

Unnamed: 17
Text

MISSING 

Distinct25
Distinct (%)75.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T10:11:43.777164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length2
Mean length2.1818182
Min length1

Characters and Unicode

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

Unique

Unique21 ?
Unique (%)63.6%

Sample

1st row학운동
2nd row5,186
3rd row11,132
4th row44
5th row22
ValueCountFrequency (%)
0 6
 
18.2%
22 2
 
6.1%
3 2
 
6.1%
44 2
 
6.1%
31 1
 
3.0%
11,132 1
 
3.0%
17 1
 
3.0%
11,122 1
 
3.0%
5,184 1
 
3.0%
1 1
 
3.0%
Other values (15) 15
45.5%
2024-02-10T10:11:44.691507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 13
18.1%
0 9
12.5%
4 9
12.5%
2 9
12.5%
3 9
12.5%
5 4
 
5.6%
, 4
 
5.6%
7 3
 
4.2%
6 3
 
4.2%
8 3
 
4.2%
Other values (5) 6
8.3%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 13
20.6%
0 9
14.3%
4 9
14.3%
2 9
14.3%
3 9
14.3%
5 4
 
6.3%
7 3
 
4.8%
6 3
 
4.8%
8 3
 
4.8%
9 1
 
1.6%
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 69
95.8%
Hangul 3
 
4.2%

Most frequent character per script

Common
ValueCountFrequency (%)
1 13
18.8%
0 9
13.0%
4 9
13.0%
2 9
13.0%
3 9
13.0%
5 4
 
5.8%
, 4
 
5.8%
7 3
 
4.3%
6 3
 
4.3%
8 3
 
4.3%
Other values (2) 3
 
4.3%
Hangul
ValueCountFrequency (%)
학 1
33.3%
운 1
33.3%
동 1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 13
18.8%
0 9
13.0%
4 9
13.0%
2 9
13.0%
3 9
13.0%
5 4
 
5.8%
, 4
 
5.8%
7 3
 
4.3%
6 3
 
4.3%
8 3
 
4.3%
Other values (2) 3
 
4.3%
Hangul
ValueCountFrequency (%)
학 1
33.3%
운 1
33.3%
동 1
33.3%

Unnamed: 18
Text

MISSING 

Distinct22
Distinct (%)66.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T10:11:45.180377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
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

Unique18 ?
Unique (%)54.5%

Sample

1st row지원1동
2nd row4,245
3rd row9,063
4th row20
5th row8
ValueCountFrequency (%)
0 8
24.2%
4 3
 
9.1%
20 2
 
6.1%
8 2
 
6.1%
21 1
 
3.0%
4,249 1
 
3.0%
3 1
 
3.0%
34 1
 
3.0%
30 1
 
3.0%
17 1
 
3.0%
Other values (12) 12
36.4%
2024-02-10T10:11:46.299199image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 15
22.4%
4 11
16.4%
3 7
10.4%
2 6
 
9.0%
8 5
 
7.5%
1 5
 
7.5%
, 4
 
6.0%
9 3
 
4.5%
6 3
 
4.5%
7 3
 
4.5%
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 (%)
0 15
25.4%
4 11
18.6%
3 7
11.9%
2 6
 
10.2%
8 5
 
8.5%
1 5
 
8.5%
9 3
 
5.1%
6 3
 
5.1%
7 3
 
5.1%
5 1
 
1.7%
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 64
95.5%
Hangul 3
 
4.5%

Most frequent character per script

Common
ValueCountFrequency (%)
0 15
23.4%
4 11
17.2%
3 7
10.9%
2 6
 
9.4%
8 5
 
7.8%
1 5
 
7.8%
, 4
 
6.2%
9 3
 
4.7%
6 3
 
4.7%
7 3
 
4.7%
Other values (2) 2
 
3.1%
Hangul
ValueCountFrequency (%)
지 1
33.3%
원 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 (%)
0 15
23.4%
4 11
17.2%
3 7
10.9%
2 6
 
9.4%
8 5
 
7.8%
1 5
 
7.8%
, 4
 
6.2%
9 3
 
4.7%
6 3
 
4.7%
7 3
 
4.7%
Other values (2) 2
 
3.1%
Hangul
ValueCountFrequency (%)
지 1
33.3%
원 1
33.3%
동 1
33.3%

Unnamed: 19
Text

MISSING 

Distinct23
Distinct (%)69.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T10:11:46.718074image/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

Unique18 ?
Unique (%)54.5%

Sample

1st row지원2동
2nd row7,722
3rd row16,770
4th row110
5th row7
ValueCountFrequency (%)
0 6
18.2%
7 3
 
9.1%
1 2
 
6.1%
10 2
 
6.1%
111 2
 
6.1%
76 1
 
3.0%
186 1
 
3.0%
91 1
 
3.0%
7,729 1
 
3.0%
33 1
 
3.0%
Other values (13) 13
39.4%
2024-02-10T10:11:47.681278image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 19
25.0%
0 12
15.8%
7 12
15.8%
2 6
 
7.9%
6 5
 
6.6%
, 4
 
5.3%
3 4
 
5.3%
5 3
 
3.9%
9 3
 
3.9%
8 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 (%)
1 19
27.5%
0 12
17.4%
7 12
17.4%
2 6
 
8.7%
6 5
 
7.2%
3 4
 
5.8%
5 3
 
4.3%
9 3
 
4.3%
8 3
 
4.3%
4 2
 
2.9%
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 73
96.1%
Hangul 3
 
3.9%

Most frequent character per script

Common
ValueCountFrequency (%)
1 19
26.0%
0 12
16.4%
7 12
16.4%
2 6
 
8.2%
6 5
 
6.8%
, 4
 
5.5%
3 4
 
5.5%
5 3
 
4.1%
9 3
 
4.1%
8 3
 
4.1%
Hangul
ValueCountFrequency (%)
지 1
33.3%
원 1
33.3%
동 1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 19
26.0%
0 12
16.4%
7 12
16.4%
2 6
 
8.2%
6 5
 
6.8%
, 4
 
5.5%
3 4
 
5.5%
5 3
 
4.1%
9 3
 
4.1%
8 3
 
4.1%
Hangul
ValueCountFrequency (%)
지 1
33.3%
원 1
33.3%
동 1
33.3%

Correlations

2024-02-10T10:11:48.009926image/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: 20.0001.000NaNNaN0.9401.0001.0001.0000.9251.0001.0001.0001.0001.0001.0001.0001.0000.837
Unnamed: 31.000NaN1.000NaN1.0001.0000.7900.7901.0001.0001.0000.7901.0000.8050.7901.0001.0001.000
Unnamed: 4NaNNaNNaN1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
Unnamed: 51.0000.9401.0001.0001.0000.9910.9850.9920.9920.9920.9940.9940.9910.9900.9910.9920.9900.991
Unnamed: 61.0001.0001.0001.0000.9911.0000.9950.9941.0000.9920.9970.9940.9990.9750.9990.9920.9950.996
Unnamed: 71.0001.0000.7901.0000.9850.9951.0000.9941.0000.9970.9920.9961.0000.9800.9890.9960.9970.991
Unnamed: 81.0001.0000.7901.0000.9920.9940.9941.0000.9970.9950.9850.9950.9940.9900.9890.9990.9930.989
Unnamed: 91.0000.9251.0001.0000.9921.0001.0000.9971.0000.9920.9941.0001.0000.9850.9970.9961.0000.991
Unnamed: 101.0001.0001.0001.0000.9920.9920.9970.9950.9921.0000.9900.9980.9960.9880.9900.9930.9980.992
Unnamed: 111.0001.0001.0001.0000.9940.9970.9920.9850.9940.9901.0000.9940.9990.9680.9960.9890.9920.992
Unnamed: 131.0001.0000.7901.0000.9940.9940.9960.9951.0000.9980.9941.0001.0000.9940.9910.9970.9940.985
Unnamed: 141.0001.0001.0001.0000.9910.9991.0000.9941.0000.9960.9991.0001.0000.9810.9990.9960.9980.996
Unnamed: 151.0001.0000.8051.0000.9900.9750.9800.9900.9850.9880.9680.9940.9811.0000.9790.9930.9830.978
Unnamed: 161.0001.0000.7901.0000.9910.9990.9890.9890.9970.9900.9960.9910.9990.9791.0000.9900.9930.994
Unnamed: 171.0001.0001.0001.0000.9920.9920.9960.9990.9960.9930.9890.9970.9960.9930.9901.0000.9930.986
Unnamed: 181.0001.0001.0001.0000.9900.9950.9970.9931.0000.9980.9920.9940.9980.9830.9930.9931.0000.993
Unnamed: 191.0000.8371.0001.0000.9910.9960.9910.9890.9910.9920.9920.9850.9960.9780.9940.9860.9931.000

Missing values

2024-02-10T10:11:19.927581image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-02-10T10:11:20.771644image/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.
2024-02-10T10:11:21.606730image/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>2023.08.30<NA><NA><NA><NA><NA><NA><NA>
1<NA>작성기준 :<NA>2023.06 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>54,8054,1802,4415,8115,5274,3834,714<NA>2,4262,3832,2553,5325,1864,2457,722
4<NA>전월말인구수<NA><NA><NA>106,5955,3163,71610,56113,0938,1659,957<NA>4,1224,3402,9567,40411,1329,06316,770
5<NA>전월말거주불명자수<NA><NA><NA>7093711877276226<NA>42954834420110
6<NA>전월말재외국민등록자수<NA><NA><NA>10867121266<NA>37392287
7<NA>증 가 요 인전 입계<NA>1,201125591001699368<NA>724565627978186
8<NA><NA><NA>남자<NA>622583455844532<NA>43303231474091
9<NA><NA><NA>여자<NA>579672545854836<NA>29153331323895
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>5000000<NA>0011300
26<NA><NA>국외<NA><NA>0000000<NA>0000000
27<NA><NA>기타<NA><NA>0000000<NA>0000000
28<NA>세대수증감<NA><NA><NA>77238-10231-6<NA>21-3101-247
29<NA>인구수증감<NA><NA><NA>71268-1249-15-20<NA>21-510-11-10-333
30<NA>거주불명자수증감<NA><NA><NA>7003010<NA>0010101
31<NA>금월말세대수<NA><NA><NA>54,8824,2032,4495,8015,5504,3844,708<NA>2,4472,3802,2653,5335,1844,2497,729
32<NA>금월말인구수<NA><NA><NA>106,6665,3423,72410,54913,1428,1509,937<NA>4,1434,3352,9667,39311,1229,06016,803
33<NA>금월말거주불명자수<NA><NA><NA>7163711880276326<NA>42955834520111
34<NA>금월말재외국민등록자수<NA><NA><NA>10867121266<NA>37392287

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