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

Description2023-12-21
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 10:14:16.437877
Analysis finished2024-02-10 10:14:22.430542
Duration5.99 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
2024-02-10T10:14:22.766339image/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%
2024-02-10T10:14:23.809625image/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
2024-02-10T10:14:24.192745image/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%
2024-02-10T10:14:25.203947image/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
2024-02-10T10:14:25.588280image/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 row2023.09 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%
2023.09 1
7.1%
현재 1
7.1%
2024-02-10T10:14:26.422354image/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%
9 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%
9 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%
9 1
 
10.0%
. 1
 
10.0%

Unnamed: 4
Text

MISSING 

Distinct2
Distinct (%)50.0%
Missing31
Missing (%)88.6%
Memory size412.0 B
2024-02-10T10:14:26.736615image/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%
2024-02-10T10:14:27.596281image/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
2024-02-10T10:14:28.052480image/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 row55,009
3rd row106,704
4th row702
5th row113
ValueCountFrequency (%)
0 6
 
17.6%
205 2
 
5.9%
1,066 1
 
2.9%
697 1
 
2.9%
106,675 1
 
2.9%
54,985 1
 
2.9%
5 1
 
2.9%
29 1
 
2.9%
24 1
 
2.9%
73 1
 
2.9%
Other values (18) 18
52.9%
2024-02-10T10:14:28.865257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 16
15.8%
5 15
14.9%
1 10
9.9%
2 9
8.9%
4 9
8.9%
6 8
7.9%
3 7
6.9%
, 6
 
5.9%
9 6
 
5.9%
7 6
 
5.9%
Other values (5) 9
8.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 88
87.1%
Other Punctuation 6
 
5.9%
Dash Punctuation 3
 
3.0%
Space Separator 2
 
2.0%
Other Letter 2
 
2.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 16
18.2%
5 15
17.0%
1 10
11.4%
2 9
10.2%
4 9
10.2%
6 8
9.1%
3 7
8.0%
9 6
 
6.8%
7 6
 
6.8%
8 2
 
2.3%
Other Letter
ValueCountFrequency (%)
1
50.0%
1
50.0%
Other Punctuation
ValueCountFrequency (%)
, 6
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
0 16
16.2%
5 15
15.2%
1 10
10.1%
2 9
9.1%
4 9
9.1%
6 8
8.1%
3 7
7.1%
, 6
 
6.1%
9 6
 
6.1%
7 6
 
6.1%
Other values (3) 7
7.1%
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 (%)
0 16
16.2%
5 15
15.2%
1 10
10.1%
2 9
9.1%
4 9
9.1%
6 8
8.1%
3 7
7.1%
, 6
 
6.1%
9 6
 
6.1%
7 6
 
6.1%
Other values (3) 7
7.1%
Hangul
ValueCountFrequency (%)
1
50.0%
1
50.0%

Unnamed: 6
Text

MISSING 

Distinct24
Distinct (%)72.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T10:14:29.282356image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
Mean length2.1212121
Min length1

Characters and Unicode

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

Unique

Unique21 ?
Unique (%)63.6%

Sample

1st row충장동
2nd row4,259
3rd row5,387
4th row39
5th row6
ValueCountFrequency (%)
0 8
24.2%
6 2
 
6.1%
39 2
 
6.1%
50 1
 
3.0%
61 1
 
3.0%
5,365 1
 
3.0%
4,251 1
 
3.0%
3 1
 
3.0%
22 1
 
3.0%
8 1
 
3.0%
Other values (14) 14
42.4%
2024-02-10T10:14:30.352384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 11
15.7%
0 9
12.9%
2 8
11.4%
5 8
11.4%
1 6
8.6%
6 5
7.1%
4 5
7.1%
9 4
 
5.7%
, 4
 
5.7%
- 3
 
4.3%
Other values (5) 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 (%)
3 11
18.3%
0 9
15.0%
2 8
13.3%
5 8
13.3%
1 6
10.0%
6 5
8.3%
4 5
8.3%
9 4
 
6.7%
8 2
 
3.3%
7 2
 
3.3%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
3 11
16.4%
0 9
13.4%
2 8
11.9%
5 8
11.9%
1 6
9.0%
6 5
7.5%
4 5
7.5%
9 4
 
6.0%
, 4
 
6.0%
- 3
 
4.5%
Other values (2) 4
 
6.0%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 11
16.4%
0 9
13.4%
2 8
11.9%
5 8
11.9%
1 6
9.0%
6 5
7.5%
4 5
7.5%
9 4
 
6.0%
, 4
 
6.0%
- 3
 
4.5%
Other values (2) 4
 
6.0%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 7
Text

MISSING 

Distinct21
Distinct (%)63.6%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T10:14:30.987477image/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

Unique16 ?
Unique (%)48.5%

Sample

1st row동명동
2nd row2,448
3rd row3,713
4th row118
5th row7
ValueCountFrequency (%)
0 9
27.3%
7 2
 
6.1%
1 2
 
6.1%
31 2
 
6.1%
118 2
 
6.1%
23 1
 
3.0%
66 1
 
3.0%
2,449 1
 
3.0%
3 1
 
3.0%
19 1
 
3.0%
Other values (11) 11
33.3%
2024-02-10T10:14:31.948597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 13
19.4%
0 10
14.9%
3 9
13.4%
2 6
9.0%
7 5
 
7.5%
4 5
 
7.5%
8 4
 
6.0%
, 4
 
6.0%
6 4
 
6.0%
2
 
3.0%
Other values (3) 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 (%)
1 13
21.7%
0 10
16.7%
3 9
15.0%
2 6
10.0%
7 5
 
8.3%
4 5
 
8.3%
8 4
 
6.7%
6 4
 
6.7%
5 2
 
3.3%
9 2
 
3.3%
Other Letter
ValueCountFrequency (%)
2
66.7%
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 (%)
1 13
20.3%
0 10
15.6%
3 9
14.1%
2 6
9.4%
7 5
 
7.8%
4 5
 
7.8%
8 4
 
6.2%
, 4
 
6.2%
6 4
 
6.2%
5 2
 
3.1%
Hangul
ValueCountFrequency (%)
2
66.7%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 13
20.3%
0 10
15.6%
3 9
14.1%
2 6
9.4%
7 5
 
7.8%
4 5
 
7.8%
8 4
 
6.2%
, 4
 
6.2%
6 4
 
6.2%
5 2
 
3.1%
Hangul
ValueCountFrequency (%)
2
66.7%
1
33.3%

Unnamed: 8
Text

MISSING 

Distinct27
Distinct (%)81.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T10:14:32.489253image/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

Unique25 ?
Unique (%)75.8%

Sample

1st row계림1동
2nd row5,780
3rd row10,497
4th row78
5th row11
ValueCountFrequency (%)
0 6
 
18.2%
76 2
 
6.1%
1 1
 
3.0%
153 1
 
3.0%
10,445 1
 
3.0%
5,749 1
 
3.0%
2 1
 
3.0%
52 1
 
3.0%
31 1
 
3.0%
7 1
 
3.0%
Other values (17) 17
51.5%
2024-02-10T10:14:33.528202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 11
14.3%
0 10
13.0%
7 9
11.7%
5 9
11.7%
2 8
10.4%
4 6
7.8%
9 5
6.5%
, 4
 
5.2%
8 4
 
5.2%
3 3
 
3.9%
Other values (5) 8
10.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 67
87.0%
Other Punctuation 4
 
5.2%
Dash Punctuation 3
 
3.9%
Other Letter 3
 
3.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 11
16.4%
0 10
14.9%
7 9
13.4%
5 9
13.4%
2 8
11.9%
4 6
9.0%
9 5
7.5%
8 4
 
6.0%
3 3
 
4.5%
6 2
 
3.0%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
1 11
14.9%
0 10
13.5%
7 9
12.2%
5 9
12.2%
2 8
10.8%
4 6
8.1%
9 5
6.8%
, 4
 
5.4%
8 4
 
5.4%
3 3
 
4.1%
Other values (2) 5
6.8%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 11
14.9%
0 10
13.5%
7 9
12.2%
5 9
12.2%
2 8
10.8%
4 6
8.1%
9 5
6.8%
, 4
 
5.4%
8 4
 
5.4%
3 3
 
4.1%
Other values (2) 5
6.8%
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
2024-02-10T10:14:33.862762image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length2
Mean length2.2424242
Min length1

Characters and Unicode

Total characters74
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 row5,623
3rd row13,288
4th row27
5th row12
ValueCountFrequency (%)
0 8
24.2%
27 3
 
9.1%
12 2
 
6.1%
36 1
 
3.0%
13,288 1
 
3.0%
5,623 1
 
3.0%
13,353 1
 
3.0%
5,658 1
 
3.0%
65 1
 
3.0%
35 1
 
3.0%
Other values (13) 13
39.4%
2024-02-10T10:14:34.843536image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 10
13.5%
0 9
12.2%
2 9
12.2%
1 9
12.2%
5 7
9.5%
6 6
8.1%
9 5
6.8%
8 5
6.8%
7 4
 
5.4%
, 4
 
5.4%
Other values (4) 6
8.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 67
90.5%
Other Punctuation 4
 
5.4%
Other Letter 3
 
4.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 10
14.9%
0 9
13.4%
2 9
13.4%
1 9
13.4%
5 7
10.4%
6 6
9.0%
9 5
7.5%
8 5
7.5%
7 4
 
6.0%
4 3
 
4.5%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
3 10
14.1%
0 9
12.7%
2 9
12.7%
1 9
12.7%
5 7
9.9%
6 6
8.5%
9 5
7.0%
8 5
7.0%
7 4
 
5.6%
, 4
 
5.6%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 10
14.1%
0 9
12.7%
2 9
12.7%
1 9
12.7%
5 7
9.9%
6 6
8.5%
9 5
7.0%
8 5
7.0%
7 4
 
5.6%
, 4
 
5.6%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 10
Text

MISSING 

Distinct25
Distinct (%)73.5%
Missing1
Missing (%)2.9%
Memory size412.0 B
2024-02-10T10:14:35.283509image/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

Unique22 ?
Unique (%)64.7%

Sample

1st row출력일자 :
2nd row산수1동
3rd row4,367
4th row8,105
5th row62
ValueCountFrequency (%)
0 8
22.9%
62 2
 
5.7%
6 2
 
5.7%
97 1
 
2.9%
3 1
 
2.9%
4,347 1
 
2.9%
41 1
 
2.9%
20 1
 
2.9%
7 1
 
2.9%
18 1
 
2.9%
Other values (16) 16
45.7%
2024-02-10T10:14:36.343697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 12
15.8%
4 11
14.5%
2 7
9.2%
6 7
9.2%
1 6
7.9%
3 5
 
6.6%
8 4
 
5.3%
7 4
 
5.3%
, 4
 
5.3%
9 3
 
3.9%
Other values (11) 13
17.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 61
80.3%
Other Letter 7
 
9.2%
Other Punctuation 5
 
6.6%
Dash Punctuation 2
 
2.6%
Space Separator 1
 
1.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 12
19.7%
4 11
18.0%
2 7
11.5%
6 7
11.5%
1 6
9.8%
3 5
8.2%
8 4
 
6.6%
7 4
 
6.6%
9 3
 
4.9%
5 2
 
3.3%
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 69
90.8%
Hangul 7
 
9.2%

Most frequent character per script

Common
ValueCountFrequency (%)
0 12
17.4%
4 11
15.9%
2 7
10.1%
6 7
10.1%
1 6
8.7%
3 5
7.2%
8 4
 
5.8%
7 4
 
5.8%
, 4
 
5.8%
9 3
 
4.3%
Other values (4) 6
8.7%
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 69
90.8%
Hangul 7
 
9.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 12
17.4%
4 11
15.9%
2 7
10.1%
6 7
10.1%
1 6
8.7%
3 5
7.2%
8 4
 
5.8%
7 4
 
5.8%
, 4
 
5.8%
9 3
 
4.3%
Other values (4) 6
8.7%
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 

Distinct26
Distinct (%)78.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T10:14:36.847917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length2.1212121
Min length1

Characters and Unicode

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

Unique

Unique24 ?
Unique (%)72.7%

Sample

1st row산수2동
2nd row4,703
3rd row9,914
4th row24
5th row7
ValueCountFrequency (%)
0 7
21.2%
13 2
 
6.1%
7 2
 
6.1%
3 1
 
3.0%
45 1
 
3.0%
9,873 1
 
3.0%
4,690 1
 
3.0%
1 1
 
3.0%
41 1
 
3.0%
8 1
 
3.0%
Other values (15) 15
45.5%
2024-02-10T10:14:37.959626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 9
12.9%
4 9
12.9%
2 8
11.4%
7 7
10.0%
1 7
10.0%
9 6
8.6%
3 6
8.6%
, 4
5.7%
6 4
5.7%
5 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 (%)
0 9
14.8%
4 9
14.8%
2 8
13.1%
7 7
11.5%
1 7
11.5%
9 6
9.8%
3 6
9.8%
6 4
6.6%
5 3
 
4.9%
8 2
 
3.3%
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 67
95.7%
Hangul 3
 
4.3%

Most frequent character per script

Common
ValueCountFrequency (%)
0 9
13.4%
4 9
13.4%
2 8
11.9%
7 7
10.4%
1 7
10.4%
9 6
9.0%
3 6
9.0%
, 4
6.0%
6 4
6.0%
5 3
 
4.5%
Other values (2) 4
6.0%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 9
13.4%
4 9
13.4%
2 8
11.9%
7 7
10.4%
1 7
10.4%
9 6
9.0%
3 6
9.0%
, 4
6.0%
6 4
6.0%
5 3
 
4.5%
Other values (2) 4
6.0%
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
Minimum2023-10-25 00:00:00
Maximum2023-10-25 00:00:00
2024-02-10T10:14:38.426822image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-10T10:14:38.964032image/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
2024-02-10T10:14:39.337633image/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

Unique17 ?
Unique (%)51.5%

Sample

1st row지산1동
2nd row2,459
3rd row4,145
4th row42
5th row3
ValueCountFrequency (%)
0 9
27.3%
3 3
 
9.1%
42 2
 
6.1%
10 2
 
6.1%
14 1
 
3.0%
40 1
 
3.0%
2,462 1
 
3.0%
1 1
 
3.0%
4 1
 
3.0%
12 1
 
3.0%
Other values (11) 11
33.3%
2024-02-10T10:14:40.256518image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4 13
19.4%
0 12
17.9%
1 12
17.9%
2 8
11.9%
3 4
 
6.0%
, 4
 
6.0%
5 3
 
4.5%
6 3
 
4.5%
8 2
 
3.0%
7 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 (%)
4 13
22.0%
0 12
20.3%
1 12
20.3%
2 8
13.6%
3 4
 
6.8%
5 3
 
5.1%
6 3
 
5.1%
8 2
 
3.4%
7 1
 
1.7%
9 1
 
1.7%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
4 13
20.3%
0 12
18.8%
1 12
18.8%
2 8
12.5%
3 4
 
6.2%
, 4
 
6.2%
5 3
 
4.7%
6 3
 
4.7%
8 2
 
3.1%
7 1
 
1.6%
Other values (2) 2
 
3.1%
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 (%)
4 13
20.3%
0 12
18.8%
1 12
18.8%
2 8
12.5%
3 4
 
6.2%
, 4
 
6.2%
5 3
 
4.7%
6 3
 
4.7%
8 2
 
3.1%
7 1
 
1.6%
Other values (2) 2
 
3.1%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 14
Text

MISSING 

Distinct20
Distinct (%)60.6%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T10:14:40.690051image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length1
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

Unique15 ?
Unique (%)45.5%

Sample

1st row지산2동
2nd row2,387
3rd row4,339
4th row9
5th row7
ValueCountFrequency (%)
0 9
27.3%
9 3
 
9.1%
20 2
 
6.1%
7 2
 
6.1%
3 2
 
6.1%
19 2
 
6.1%
26 1
 
3.0%
2,373 1
 
3.0%
14 1
 
3.0%
6 1
 
3.0%
Other values (9) 9
27.3%
2024-02-10T10:14:41.623163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 11
16.9%
3 9
13.8%
9 7
10.8%
1 7
10.8%
2 7
10.8%
7 4
 
6.2%
4 4
 
6.2%
, 4
 
6.2%
6 3
 
4.6%
5 2
 
3.1%
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 11
19.6%
3 9
16.1%
9 7
12.5%
1 7
12.5%
2 7
12.5%
7 4
 
7.1%
4 4
 
7.1%
6 3
 
5.4%
5 2
 
3.6%
8 2
 
3.6%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
0 11
17.7%
3 9
14.5%
9 7
11.3%
1 7
11.3%
2 7
11.3%
7 4
 
6.5%
4 4
 
6.5%
, 4
 
6.5%
6 3
 
4.8%
5 2
 
3.2%
Other values (2) 4
 
6.5%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 11
17.7%
3 9
14.5%
9 7
11.3%
1 7
11.3%
2 7
11.3%
7 4
 
6.5%
4 4
 
6.5%
, 4
 
6.5%
6 3
 
4.8%
5 2
 
3.2%
Other values (2) 4
 
6.5%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 15
Text

MISSING 

Distinct25
Distinct (%)75.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T10:14:41.990623image/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

Unique22 ?
Unique (%)66.7%

Sample

1st row서남동
2nd row2,302
3rd row3,012
4th row53
5th row4
ValueCountFrequency (%)
0 7
21.2%
12 2
 
6.1%
1 2
 
6.1%
28 2
 
6.1%
24 1
 
3.0%
18 1
 
3.0%
52 1
 
3.0%
3,023 1
 
3.0%
2,310 1
 
3.0%
11 1
 
3.0%
Other values (14) 14
42.4%
2024-02-10T10:14:43.049679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 13
19.4%
2 13
19.4%
1 11
16.4%
3 8
11.9%
8 4
 
6.0%
, 4
 
6.0%
5 4
 
6.0%
4 3
 
4.5%
6 1
 
1.5%
9 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 (%)
0 13
22.0%
2 13
22.0%
1 11
18.6%
3 8
13.6%
8 4
 
6.8%
5 4
 
6.8%
4 3
 
5.1%
6 1
 
1.7%
9 1
 
1.7%
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 (%)
- 1
100.0%

Most occurring scripts

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

Most frequent character per script

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

Unnamed: 16
Text

MISSING 

Distinct23
Distinct (%)69.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T10:14:43.382256image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length2
Mean length2.0606061
Min length1

Characters and Unicode

Total characters68
Distinct characters13
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 row3,527
3rd row7,360
4th row77
5th row10
ValueCountFrequency (%)
0 7
21.2%
31 2
 
6.1%
77 2
 
6.1%
10 2
 
6.1%
1 2
 
6.1%
79 1
 
3.0%
39 1
 
3.0%
3,524 1
 
3.0%
4 1
 
3.0%
3 1
 
3.0%
Other values (13) 13
39.4%
2024-02-10T10:14:44.344861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 11
16.2%
3 10
14.7%
7 9
13.2%
1 8
11.8%
4 6
8.8%
2 6
8.8%
5 4
 
5.9%
, 4
 
5.9%
6 3
 
4.4%
9 3
 
4.4%
Other values (3) 4
 
5.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 60
88.2%
Other Punctuation 4
 
5.9%
Dash Punctuation 2
 
2.9%
Other Letter 2
 
2.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 11
18.3%
3 10
16.7%
7 9
15.0%
1 8
13.3%
4 6
10.0%
2 6
10.0%
5 4
 
6.7%
6 3
 
5.0%
9 3
 
5.0%
Other Letter
ValueCountFrequency (%)
1
50.0%
1
50.0%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 66
97.1%
Hangul 2
 
2.9%

Most frequent character per script

Common
ValueCountFrequency (%)
0 11
16.7%
3 10
15.2%
7 9
13.6%
1 8
12.1%
4 6
9.1%
2 6
9.1%
5 4
 
6.1%
, 4
 
6.1%
6 3
 
4.5%
9 3
 
4.5%
Hangul
ValueCountFrequency (%)
1
50.0%
1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 66
97.1%
Hangul 2
 
2.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 11
16.7%
3 10
15.2%
7 9
13.6%
1 8
12.1%
4 6
9.1%
2 6
9.1%
5 4
 
6.1%
, 4
 
6.1%
6 3
 
4.5%
9 3
 
4.5%
Hangul
ValueCountFrequency (%)
1
50.0%
1
50.0%

Unnamed: 17
Text

MISSING 

Distinct24
Distinct (%)72.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T10:14:44.695029image/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 row5,187
3rd row11,095
4th row45
5th row24
ValueCountFrequency (%)
0 8
24.2%
45 2
 
6.1%
24 2
 
6.1%
14 1
 
3.0%
11,095 1
 
3.0%
39 1
 
3.0%
5,185 1
 
3.0%
15 1
 
3.0%
2 1
 
3.0%
10 1
 
3.0%
Other values (14) 14
42.4%
2024-02-10T10:14:45.599531image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 12
16.7%
1 10
13.9%
5 9
12.5%
4 7
9.7%
3 7
9.7%
2 6
8.3%
8 4
 
5.6%
, 4
 
5.6%
7 3
 
4.2%
9 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 12
19.0%
1 10
15.9%
5 9
14.3%
4 7
11.1%
3 7
11.1%
2 6
9.5%
8 4
 
6.3%
7 3
 
4.8%
9 3
 
4.8%
6 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 12
17.4%
1 10
14.5%
5 9
13.0%
4 7
10.1%
3 7
10.1%
2 6
8.7%
8 4
 
5.8%
, 4
 
5.8%
7 3
 
4.3%
9 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 12
17.4%
1 10
14.5%
5 9
13.0%
4 7
10.1%
3 7
10.1%
2 6
8.7%
8 4
 
5.8%
, 4
 
5.8%
7 3
 
4.3%
9 3
 
4.3%
Other values (2) 4
 
5.8%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 18
Text

MISSING 

Distinct21
Distinct (%)63.6%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T10:14:45.997530image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
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

Unique18 ?
Unique (%)54.5%

Sample

1st row지원1동
2nd row4,274
3rd row9,089
4th row22
5th row9
ValueCountFrequency (%)
0 8
24.2%
22 4
 
12.1%
9 3
 
9.1%
30 1
 
3.0%
4,276 1
 
3.0%
2 1
 
3.0%
21 1
 
3.0%
12 1
 
3.0%
27 1
 
3.0%
28 1
 
3.0%
Other values (11) 11
33.3%
2024-02-10T10:14:46.848397image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 15
22.4%
0 11
16.4%
1 9
13.4%
9 6
 
9.0%
4 6
 
9.0%
, 4
 
6.0%
7 4
 
6.0%
8 3
 
4.5%
5 3
 
4.5%
3 2
 
3.0%
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 (%)
2 15
25.0%
0 11
18.3%
1 9
15.0%
9 6
 
10.0%
4 6
 
10.0%
7 4
 
6.7%
8 3
 
5.0%
5 3
 
5.0%
3 2
 
3.3%
6 1
 
1.7%
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 (%)
2 15
23.4%
0 11
17.2%
1 9
14.1%
9 6
 
9.4%
4 6
 
9.4%
, 4
 
6.2%
7 4
 
6.2%
8 3
 
4.7%
5 3
 
4.7%
3 2
 
3.1%
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 (%)
2 15
23.4%
0 11
17.2%
1 9
14.1%
9 6
 
9.4%
4 6
 
9.4%
, 4
 
6.2%
7 4
 
6.2%
8 3
 
4.7%
5 3
 
4.7%
3 2
 
3.1%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 19
Text

MISSING 

Distinct24
Distinct (%)72.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T10:14:47.399127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.2727273
Min length1

Characters and Unicode

Total characters75
Distinct characters14
Distinct categories3 ?
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 row지원2동
2nd row7,693
3rd row16,760
4th row106
5th row7
ValueCountFrequency (%)
0 8
24.2%
106 2
 
6.1%
7 2
 
6.1%
11 1
 
3.0%
16,760 1
 
3.0%
54 1
 
3.0%
7,711 1
 
3.0%
66 1
 
3.0%
18 1
 
3.0%
8 1
 
3.0%
Other values (14) 14
42.4%
2024-02-10T10:14:48.274876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 14
18.7%
6 13
17.3%
0 11
14.7%
7 9
12.0%
8 7
9.3%
2 4
 
5.3%
, 4
 
5.3%
9 3
 
4.0%
3 3
 
4.0%
4 3
 
4.0%
Other values (4) 4
 
5.3%

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%
6 13
19.1%
0 11
16.2%
7 9
13.2%
8 7
10.3%
2 4
 
5.9%
9 3
 
4.4%
3 3
 
4.4%
4 3
 
4.4%
5 1
 
1.5%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
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%
6 13
18.1%
0 11
15.3%
7 9
12.5%
8 7
9.7%
2 4
 
5.6%
, 4
 
5.6%
9 3
 
4.2%
3 3
 
4.2%
4 3
 
4.2%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 14
19.4%
6 13
18.1%
0 11
15.3%
7 9
12.5%
8 7
9.7%
2 4
 
5.6%
, 4
 
5.6%
9 3
 
4.2%
3 3
 
4.2%
4 3
 
4.2%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Correlations

2024-02-10T10:14:48.921549image/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: 31.000NaN1.000NaN1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0000.7901.0001.0001.000
Unnamed: 4NaNNaNNaN1.0001.0001.0001.0001.0001.0001.0001.0000.0001.0001.0001.0001.0001.0001.000
Unnamed: 51.0001.0001.0001.0001.0000.9930.9910.9990.9920.9930.9940.9930.9921.0000.9920.9930.9910.993
Unnamed: 61.0001.0001.0001.0000.9931.0000.9950.9930.9880.9981.0000.9950.9960.9890.9900.9980.9880.998
Unnamed: 71.0001.0001.0001.0000.9910.9951.0000.9930.9911.0001.0000.9990.9910.9810.9941.0000.9951.000
Unnamed: 81.0001.0001.0001.0000.9990.9930.9931.0000.9950.9950.9940.9930.9930.9950.9940.9950.9950.995
Unnamed: 91.0001.0001.0001.0000.9920.9880.9910.9951.0000.9960.9950.9920.9910.9780.9980.9960.9900.996
Unnamed: 101.0001.0001.0001.0000.9930.9981.0000.9950.9961.0001.0001.0001.0000.9740.9971.0001.0001.000
Unnamed: 111.0001.0001.0001.0000.9941.0001.0000.9940.9951.0001.0001.0001.0000.9860.9971.0001.0001.000
Unnamed: 131.0001.0001.0000.0000.9930.9950.9990.9930.9921.0001.0001.0000.9870.9840.9941.0000.9941.000
Unnamed: 141.0001.0001.0001.0000.9920.9960.9910.9930.9911.0001.0000.9871.0000.9840.9931.0000.9851.000
Unnamed: 151.0001.0001.0001.0001.0000.9890.9810.9950.9780.9740.9860.9840.9841.0000.9770.9740.9600.974
Unnamed: 161.0001.0000.7901.0000.9920.9900.9940.9940.9980.9970.9970.9940.9930.9771.0000.9970.9890.997
Unnamed: 171.0001.0001.0001.0000.9930.9981.0000.9950.9961.0001.0001.0001.0000.9740.9971.0001.0001.000
Unnamed: 181.0001.0001.0001.0000.9910.9880.9950.9950.9901.0001.0000.9940.9850.9600.9891.0001.0001.000
Unnamed: 191.0001.0001.0001.0000.9930.9981.0000.9950.9961.0001.0001.0001.0000.9740.9971.0001.0001.000

Missing values

2024-02-10T10:14:20.058428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-02-10T10:14:21.034770image/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.
2024-02-10T10:14:21.749832image/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>2023.10.25<NA><NA><NA><NA><NA><NA><NA>
1<NA>작성기준 :<NA>2023.09 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>55,0094,2592,4485,7805,6234,3674,703<NA>2,4592,3872,3023,5275,1874,2747,693
4<NA>전월말인구수<NA><NA><NA>106,7045,3873,71310,49713,2888,1059,914<NA>4,1454,3393,0127,36011,0959,08916,760
5<NA>전월말거주불명자수<NA><NA><NA>7023911878276224<NA>42953774522106
6<NA>전월말재외국민등록자수<NA><NA><NA>11367111267<NA>374102497
7<NA>증 가 요 인전 입<NA>1,06893701021476056<NA>432859756881186
8<NA><NA><NA>남자<NA>546394254613129<NA>28152844434488
9<NA><NA><NA>여자<NA>522542848862927<NA>15133131253798
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>-24-81-3135-20-13<NA>3-148-3-2218
29<NA>인구수증감<NA><NA><NA>-29-223-5265-41-41<NA>-1-2011-4-152266
30<NA>거주불명자수증감<NA><NA><NA>-5-30-2001<NA>00-10000
31<NA>금월말세대수<NA><NA><NA>54,9854,2512,4495,7495,6584,3474,690<NA>2,4622,3732,3103,5245,1854,2767,711
32<NA>금월말인구수<NA><NA><NA>106,6755,3653,71610,44513,3538,0649,873<NA>4,1444,3193,0237,35611,0809,11116,826
33<NA>금월말거주불명자수<NA><NA><NA>6973611876276225<NA>42952774522106
34<NA>금월말재외국민등록자수<NA><NA><NA>11467121167<NA>375102497

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