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

Description2024-02-01
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 10:15:27.530664
Analysis finished2024-02-10 10:15:33.600598
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
Distinct16
Distinct (%)100.0%
Missing19
Missing (%)54.3%
Memory size412.0 B
2024-02-10T10:15:33.822332image/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%
2024-02-10T10:15:34.810649image/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
2024-02-10T10:15:35.172337image/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%
2024-02-10T10:15:36.156880image/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
2024-02-10T10:15:36.631792image/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 row2023.11 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%
2023.11 1
7.1%
현재 1
7.1%
2024-02-10T10:15:37.503339image/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 (%)
1 2
33.3%
2 2
33.3%
3 1
16.7%
0 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%
1 2
20.0%
2 2
20.0%
3 1
 
10.0%
. 1
 
10.0%
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%
1 2
20.0%
2 2
20.0%
3 1
 
10.0%
. 1
 
10.0%
0 1
 
10.0%

Unnamed: 4
Text

MISSING 

Distinct2
Distinct (%)50.0%
Missing31
Missing (%)88.6%
Memory size412.0 B
2024-02-10T10:15:38.042179image/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%
2024-02-10T10:15:38.890776image/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
2024-02-10T10:15:39.401255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length3.0606061
Min length1

Characters and Unicode

Total characters101
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

Unique23 ?
Unique (%)69.7%

Sample

1st row합 계
2nd row55,107
3rd row106,957
4th row634
5th row113
ValueCountFrequency (%)
0 4
 
11.8%
270 2
 
5.9%
1 2
 
5.9%
113 2
 
5.9%
623 1
 
2.9%
1,212 1
 
2.9%
107,165 1
 
2.9%
55,243 1
 
2.9%
208 1
 
2.9%
136 1
 
2.9%
Other values (18) 18
52.9%
2024-02-10T10:15:40.546436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 15
14.9%
5 12
11.9%
0 10
9.9%
3 10
9.9%
2 10
9.9%
7 10
9.9%
6 9
8.9%
8 7
6.9%
, 6
 
5.9%
9 4
 
4.0%
Other values (4) 8
7.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 91
90.1%
Other Punctuation 6
 
5.9%
Space Separator 2
 
2.0%
Other Letter 2
 
2.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 15
16.5%
5 12
13.2%
0 10
11.0%
3 10
11.0%
2 10
11.0%
7 10
11.0%
6 9
9.9%
8 7
7.7%
9 4
 
4.4%
4 4
 
4.4%
Other Letter
ValueCountFrequency (%)
1
50.0%
1
50.0%
Other Punctuation
ValueCountFrequency (%)
, 6
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 (%)
1 15
15.2%
5 12
12.1%
0 10
10.1%
3 10
10.1%
2 10
10.1%
7 10
10.1%
6 9
9.1%
8 7
7.1%
, 6
 
6.1%
9 4
 
4.0%
Other values (2) 6
 
6.1%
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 (%)
1 15
15.2%
5 12
12.1%
0 10
10.1%
3 10
10.1%
2 10
10.1%
7 10
10.1%
6 9
9.1%
8 7
7.1%
, 6
 
6.1%
9 4
 
4.0%
Other values (2) 6
 
6.1%
Hangul
ValueCountFrequency (%)
1
50.0%
1
50.0%

Unnamed: 6
Text

MISSING 

Distinct22
Distinct (%)66.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T10:15:41.338117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
Mean length2.1212121
Min length1

Characters and Unicode

Total characters70
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

Unique16 ?
Unique (%)48.5%

Sample

1st row충장동
2nd row4,253
3rd row5,361
4th row35
5th row6
ValueCountFrequency (%)
0 7
21.2%
1 2
 
6.1%
5 2
 
6.1%
34 2
 
6.1%
6 2
 
6.1%
59 2
 
6.1%
19 1
 
3.0%
99 1
 
3.0%
51 1
 
3.0%
4,252 1
 
3.0%
Other values (12) 12
36.4%
2024-02-10T10:15:42.358389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 13
18.6%
0 9
12.9%
1 8
11.4%
3 8
11.4%
4 7
10.0%
9 5
 
7.1%
6 5
 
7.1%
2 5
 
7.1%
, 4
 
5.7%
- 3
 
4.3%
Other values (3) 3
 
4.3%

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 (%)
5 13
21.7%
0 9
15.0%
1 8
13.3%
3 8
13.3%
4 7
11.7%
9 5
 
8.3%
6 5
 
8.3%
2 5
 
8.3%
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 (%)
5 13
19.4%
0 9
13.4%
1 8
11.9%
3 8
11.9%
4 7
10.4%
9 5
 
7.5%
6 5
 
7.5%
2 5
 
7.5%
, 4
 
6.0%
- 3
 
4.5%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 13
19.4%
0 9
13.4%
1 8
11.9%
3 8
11.9%
4 7
10.4%
9 5
 
7.5%
6 5
 
7.5%
2 5
 
7.5%
, 4
 
6.0%
- 3
 
4.5%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 7
Text

MISSING 

Distinct25
Distinct (%)75.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T10:15:42.724603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
Mean length2.1515152
Min length1

Characters and Unicode

Total characters71
Distinct characters14
Distinct 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 row동명동
2nd row2,423
3rd row3,683
4th row119
5th row7
ValueCountFrequency (%)
0 7
21.2%
25 2
 
6.1%
12 2
 
6.1%
26 2
 
6.1%
19 1
 
3.0%
136 1
 
3.0%
3,671 1
 
3.0%
2,418 1
 
3.0%
17 1
 
3.0%
5 1
 
3.0%
Other values (14) 14
42.4%
2024-02-10T10:15:43.839550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 13
18.3%
2 11
15.5%
0 8
11.3%
3 8
11.3%
6 6
8.5%
5 4
 
5.6%
, 4
 
5.6%
7 4
 
5.6%
4 3
 
4.2%
8 3
 
4.2%
Other values (4) 7
9.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 62
87.3%
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
21.0%
2 11
17.7%
0 8
12.9%
3 8
12.9%
6 6
9.7%
5 4
 
6.5%
7 4
 
6.5%
4 3
 
4.8%
8 3
 
4.8%
9 2
 
3.2%
Other Letter
ValueCountFrequency (%)
2
66.7%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 68
95.8%
Hangul 3
 
4.2%

Most frequent character per script

Common
ValueCountFrequency (%)
1 13
19.1%
2 11
16.2%
0 8
11.8%
3 8
11.8%
6 6
8.8%
5 4
 
5.9%
, 4
 
5.9%
7 4
 
5.9%
4 3
 
4.4%
8 3
 
4.4%
Other values (2) 4
 
5.9%
Hangul
ValueCountFrequency (%)
2
66.7%
1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 68
95.8%
Hangul 3
 
4.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 13
19.1%
2 11
16.2%
0 8
11.8%
3 8
11.8%
6 6
8.8%
5 4
 
5.9%
, 4
 
5.9%
7 4
 
5.9%
4 3
 
4.4%
8 3
 
4.4%
Other values (2) 4
 
5.9%
Hangul
ValueCountFrequency (%)
2
66.7%
1
33.3%

Unnamed: 8
Text

MISSING 

Distinct25
Distinct (%)75.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T10:15:44.342504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.3636364
Min length1

Characters and Unicode

Total characters78
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 row5,720
3rd row10,421
4th row76
5th row12
ValueCountFrequency (%)
0 7
21.2%
12 2
 
6.1%
76 2
 
6.1%
7 1
 
3.0%
195 1
 
3.0%
5,695 1
 
3.0%
52 1
 
3.0%
25 1
 
3.0%
5 1
 
3.0%
53 1
 
3.0%
Other values (15) 15
45.5%
2024-02-10T10:15:45.502423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 15
19.2%
0 12
15.4%
5 8
10.3%
2 7
9.0%
7 6
 
7.7%
6 6
 
7.7%
4 5
 
6.4%
, 4
 
5.1%
3 4
 
5.1%
9 4
 
5.1%
Other values (5) 7
9.0%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 15
21.7%
0 12
17.4%
5 8
11.6%
2 7
10.1%
7 6
 
8.7%
6 6
 
8.7%
4 5
 
7.2%
3 4
 
5.8%
9 4
 
5.8%
8 2
 
2.9%
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 75
96.2%
Hangul 3
 
3.8%

Most frequent character per script

Common
ValueCountFrequency (%)
1 15
20.0%
0 12
16.0%
5 8
10.7%
2 7
9.3%
7 6
 
8.0%
6 6
 
8.0%
4 5
 
6.7%
, 4
 
5.3%
3 4
 
5.3%
9 4
 
5.3%
Other values (2) 4
 
5.3%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 15
20.0%
0 12
16.0%
5 8
10.7%
2 7
9.3%
7 6
 
8.0%
6 6
 
8.0%
4 5
 
6.7%
, 4
 
5.3%
3 4
 
5.3%
9 4
 
5.3%
Other values (2) 4
 
5.3%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 9
Text

MISSING 

Distinct25
Distinct (%)75.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T10:15:45.925085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.2121212
Min length1

Characters and Unicode

Total characters73
Distinct characters13
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique22 ?
Unique (%)66.7%

Sample

1st row계림2동
2nd row5,675
3rd row13,364
4th row27
5th row11
ValueCountFrequency (%)
0 7
21.2%
11 2
 
6.1%
27 2
 
6.1%
7 1
 
3.0%
52 1
 
3.0%
5,681 1
 
3.0%
10 1
 
3.0%
6 1
 
3.0%
2 1
 
3.0%
4 1
 
3.0%
Other values (15) 15
45.5%
2024-02-10T10:15:46.788947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4 12
16.4%
0 11
15.1%
1 10
13.7%
7 7
9.6%
2 6
8.2%
3 6
8.2%
5 6
8.2%
6 5
6.8%
, 4
 
5.5%
8 3
 
4.1%
Other values (3) 3
 
4.1%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 12
18.2%
0 11
16.7%
1 10
15.2%
7 7
10.6%
2 6
9.1%
3 6
9.1%
5 6
9.1%
6 5
7.6%
8 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 70
95.9%
Hangul 3
 
4.1%

Most frequent character per script

Common
ValueCountFrequency (%)
4 12
17.1%
0 11
15.7%
1 10
14.3%
7 7
10.0%
2 6
8.6%
3 6
8.6%
5 6
8.6%
6 5
7.1%
, 4
 
5.7%
8 3
 
4.3%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
4 12
17.1%
0 11
15.7%
1 10
14.3%
7 7
10.0%
2 6
8.6%
3 6
8.6%
5 6
8.6%
6 5
7.1%
, 4
 
5.7%
8 3
 
4.3%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 10
Text

MISSING 

Distinct26
Distinct (%)76.5%
Missing1
Missing (%)2.9%
Memory size412.0 B
2024-02-10T10:15:47.214113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.1470588
Min length1

Characters and Unicode

Total characters73
Distinct characters20
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique22 ?
Unique (%)64.7%

Sample

1st row출력일자 :
2nd row산수1동
3rd row4,342
4th row8,028
5th row53
ValueCountFrequency (%)
0 6
 
17.1%
6 3
 
8.6%
1 2
 
5.7%
86 2
 
5.7%
31 1
 
2.9%
38 1
 
2.9%
8,022 1
 
2.9%
4,346 1
 
2.9%
3 1
 
2.9%
4 1
 
2.9%
Other values (16) 16
45.7%
2024-02-10T10:15:48.161782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 10
13.7%
6 9
12.3%
3 9
12.3%
4 8
11.0%
8 8
11.0%
1 6
8.2%
2 5
6.8%
, 4
 
5.5%
5 3
 
4.1%
1
 
1.4%
Other values (10) 10
13.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 59
80.8%
Other Letter 7
 
9.6%
Other Punctuation 5
 
6.8%
Space Separator 1
 
1.4%
Dash Punctuation 1
 
1.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 10
16.9%
6 9
15.3%
3 9
15.3%
4 8
13.6%
8 8
13.6%
1 6
10.2%
2 5
8.5%
5 3
 
5.1%
9 1
 
1.7%
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%
Space Separator
ValueCountFrequency (%)
1
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 66
90.4%
Hangul 7
 
9.6%

Most frequent character per script

Common
ValueCountFrequency (%)
0 10
15.2%
6 9
13.6%
3 9
13.6%
4 8
12.1%
8 8
12.1%
1 6
9.1%
2 5
7.6%
, 4
 
6.1%
5 3
 
4.5%
9 1
 
1.5%
Other values (3) 3
 
4.5%
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 66
90.4%
Hangul 7
 
9.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 10
15.2%
6 9
13.6%
3 9
13.6%
4 8
12.1%
8 8
12.1%
1 6
9.1%
2 5
7.6%
, 4
 
6.1%
5 3
 
4.5%
9 1
 
1.5%
Other values (3) 3
 
4.5%
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 

Distinct24
Distinct (%)72.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T10:15:48.497829image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length2.1212121
Min length1

Characters and Unicode

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

Unique

Unique21 ?
Unique (%)63.6%

Sample

1st row산수2동
2nd row4,678
3rd row9,871
4th row24
5th row7
ValueCountFrequency (%)
0 8
24.2%
24 2
 
6.1%
37 2
 
6.1%
7 2
 
6.1%
18 1
 
3.0%
9,871 1
 
3.0%
4,673 1
 
3.0%
5 1
 
3.0%
13 1
 
3.0%
25 1
 
3.0%
Other values (13) 13
39.4%
2024-02-10T10:15:49.440308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

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

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 (%)
7 10
16.4%
0 8
13.1%
2 8
13.1%
3 7
11.5%
4 6
9.8%
8 6
9.8%
1 5
8.2%
9 4
 
6.6%
5 4
 
6.6%
6 3
 
4.9%
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 (%)
7 10
14.9%
0 8
11.9%
2 8
11.9%
3 7
10.4%
4 6
9.0%
8 6
9.0%
1 5
7.5%
9 4
 
6.0%
, 4
 
6.0%
5 4
 
6.0%
Other values (2) 5
7.5%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
7 10
14.9%
0 8
11.9%
2 8
11.9%
3 7
10.4%
4 6
9.0%
8 6
9.0%
1 5
7.5%
9 4
 
6.0%
, 4
 
6.0%
5 4
 
6.0%
Other values (2) 5
7.5%
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
Minimum2024-01-03 00:00:00
Maximum2024-01-03 00:00:00
2024-02-10T10:15:49.970214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-10T10:15:50.266789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Unnamed: 13
Text

MISSING 

Distinct23
Distinct (%)69.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T10:15:50.546647image/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

Unique20 ?
Unique (%)60.6%

Sample

1st row지산1동
2nd row2,456
3rd row4,130
4th row45
5th row3
ValueCountFrequency (%)
0 8
24.2%
32 3
 
9.1%
3 2
 
6.1%
2 2
 
6.1%
30 1
 
3.0%
18 1
 
3.0%
4,131 1
 
3.0%
2,460 1
 
3.0%
1 1
 
3.0%
4 1
 
3.0%
Other values (12) 12
36.4%
2024-02-10T10:15:51.431650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 11
16.4%
3 10
14.9%
2 10
14.9%
1 10
14.9%
4 8
11.9%
6 5
7.5%
, 4
 
6.0%
5 2
 
3.0%
9 1
 
1.5%
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 (%)
0 11
18.6%
3 10
16.9%
2 10
16.9%
1 10
16.9%
4 8
13.6%
6 5
8.5%
5 2
 
3.4%
9 1
 
1.7%
7 1
 
1.7%
8 1
 
1.7%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
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 10
15.6%
2 10
15.6%
1 10
15.6%
4 8
12.5%
6 5
7.8%
, 4
 
6.2%
5 2
 
3.1%
9 1
 
1.6%
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 (%)
0 11
17.2%
3 10
15.6%
2 10
15.6%
1 10
15.6%
4 8
12.5%
6 5
7.8%
, 4
 
6.2%
5 2
 
3.1%
9 1
 
1.6%
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 

Distinct23
Distinct (%)69.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T10:15:51.924632image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length2.1212121
Min length1

Characters and Unicode

Total characters70
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

Unique19 ?
Unique (%)57.6%

Sample

1st row지산2동
2nd row2,366
3rd row4,296
4th row13
5th row6
ValueCountFrequency (%)
0 8
24.2%
6 3
 
9.1%
14 2
 
6.1%
17 2
 
6.1%
7 1
 
3.0%
13 1
 
3.0%
27 1
 
3.0%
4,273 1
 
3.0%
2,360 1
 
3.0%
1 1
 
3.0%
Other values (12) 12
36.4%
2024-02-10T10:15:53.023928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6 11
15.7%
2 11
15.7%
0 9
12.9%
1 9
12.9%
3 8
11.4%
7 6
8.6%
4 5
7.1%
, 4
 
5.7%
- 3
 
4.3%
9 1
 
1.4%
Other values (3) 3
 
4.3%

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 (%)
6 11
18.3%
2 11
18.3%
0 9
15.0%
1 9
15.0%
3 8
13.3%
7 6
10.0%
4 5
8.3%
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 (%)
- 3
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
6 11
16.4%
2 11
16.4%
0 9
13.4%
1 9
13.4%
3 8
11.9%
7 6
9.0%
4 5
7.5%
, 4
 
6.0%
- 3
 
4.5%
9 1
 
1.5%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
6 11
16.4%
2 11
16.4%
0 9
13.4%
1 9
13.4%
3 8
11.9%
7 6
9.0%
4 5
7.5%
, 4
 
6.0%
- 3
 
4.5%
9 1
 
1.5%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 15
Text

MISSING 

Distinct26
Distinct (%)78.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T10:15:53.381764image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
Mean length2.1515152
Min length1

Characters and Unicode

Total characters71
Distinct characters15
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique23 ?
Unique (%)69.7%

Sample

1st row서남동
2nd row2,316
3rd row3,029
4th row52
5th row5
ValueCountFrequency (%)
0 6
 
18.2%
18 2
 
6.1%
28 2
 
6.1%
5 2
 
6.1%
9 1
 
3.0%
20 1
 
3.0%
3,006 1
 
3.0%
2,288 1
 
3.0%
35 1
 
3.0%
23 1
 
3.0%
Other values (15) 15
45.5%
2024-02-10T10:15:54.298875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 12
16.9%
0 11
15.5%
1 9
12.7%
3 8
11.3%
8 7
9.9%
5 6
8.5%
, 4
 
5.6%
9 3
 
4.2%
- 3
 
4.2%
6 2
 
2.8%
Other values (5) 6
8.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 61
85.9%
Other Punctuation 4
 
5.6%
Dash Punctuation 3
 
4.2%
Other Letter 3
 
4.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 12
19.7%
0 11
18.0%
1 9
14.8%
3 8
13.1%
8 7
11.5%
5 6
9.8%
9 3
 
4.9%
6 2
 
3.3%
7 2
 
3.3%
4 1
 
1.6%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 68
95.8%
Hangul 3
 
4.2%

Most frequent character per script

Common
ValueCountFrequency (%)
2 12
17.6%
0 11
16.2%
1 9
13.2%
3 8
11.8%
8 7
10.3%
5 6
8.8%
, 4
 
5.9%
9 3
 
4.4%
- 3
 
4.4%
6 2
 
2.9%
Other values (2) 3
 
4.4%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 68
95.8%
Hangul 3
 
4.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 12
17.6%
0 11
16.2%
1 9
13.2%
3 8
11.8%
8 7
10.3%
5 6
8.8%
, 4
 
5.9%
9 3
 
4.4%
- 3
 
4.4%
6 2
 
2.9%
Other values (2) 3
 
4.4%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 16
Text

MISSING 

Distinct26
Distinct (%)78.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T10:15:54.640822image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length2
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

Unique24 ?
Unique (%)72.7%

Sample

1st row학동
2nd row3,495
3rd row7,338
4th row50
5th row10
ValueCountFrequency (%)
0 7
21.2%
10 2
 
6.1%
42 1
 
3.0%
7,335 1
 
3.0%
3,494 1
 
3.0%
14 1
 
3.0%
3 1
 
3.0%
1 1
 
3.0%
6 1
 
3.0%
26 1
 
3.0%
Other values (16) 16
48.5%
2024-02-10T10:15:55.432948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 11
15.9%
3 11
15.9%
1 8
11.6%
4 8
11.6%
7 7
10.1%
5 6
8.7%
, 4
 
5.8%
2 4
 
5.8%
6 3
 
4.3%
9 2
 
2.9%
Other values (4) 5
7.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 61
88.4%
Other Punctuation 4
 
5.8%
Dash Punctuation 2
 
2.9%
Other Letter 2
 
2.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 11
18.0%
3 11
18.0%
1 8
13.1%
4 8
13.1%
7 7
11.5%
5 6
9.8%
2 4
 
6.6%
6 3
 
4.9%
9 2
 
3.3%
8 1
 
1.6%
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 67
97.1%
Hangul 2
 
2.9%

Most frequent character per script

Common
ValueCountFrequency (%)
0 11
16.4%
3 11
16.4%
1 8
11.9%
4 8
11.9%
7 7
10.4%
5 6
9.0%
, 4
 
6.0%
2 4
 
6.0%
6 3
 
4.5%
9 2
 
3.0%
Other values (2) 3
 
4.5%
Hangul
ValueCountFrequency (%)
1
50.0%
1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 67
97.1%
Hangul 2
 
2.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 11
16.4%
3 11
16.4%
1 8
11.9%
4 8
11.9%
7 7
10.4%
5 6
9.0%
, 4
 
6.0%
2 4
 
6.0%
6 3
 
4.5%
9 2
 
3.0%
Other values (2) 3
 
4.5%
Hangul
ValueCountFrequency (%)
1
50.0%
1
50.0%

Unnamed: 17
Text

MISSING 

Distinct25
Distinct (%)75.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T10:15:55.891604image/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

Unique22 ?
Unique (%)66.7%

Sample

1st row학운동
2nd row5,160
3rd row11,056
4th row23
5th row24
ValueCountFrequency (%)
0 7
21.2%
1 2
 
6.1%
23 2
 
6.1%
53 1
 
3.0%
42 1
 
3.0%
28 1
 
3.0%
11,023 1
 
3.0%
5,161 1
 
3.0%
5 1
 
3.0%
33 1
 
3.0%
Other values (15) 15
45.5%
2024-02-10T10:15:56.731757image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 12
16.7%
1 12
16.7%
0 11
15.3%
2 8
11.1%
5 8
11.1%
, 4
 
5.6%
6 4
 
5.6%
4 4
 
5.6%
9 2
 
2.8%
8 2
 
2.8%
Other values (5) 5
6.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 64
88.9%
Other Punctuation 4
 
5.6%
Other Letter 3
 
4.2%
Dash Punctuation 1
 
1.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 12
18.8%
1 12
18.8%
0 11
17.2%
2 8
12.5%
5 8
12.5%
6 4
 
6.2%
4 4
 
6.2%
9 2
 
3.1%
8 2
 
3.1%
7 1
 
1.6%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
3 12
17.4%
1 12
17.4%
0 11
15.9%
2 8
11.6%
5 8
11.6%
, 4
 
5.8%
6 4
 
5.8%
4 4
 
5.8%
9 2
 
2.9%
8 2
 
2.9%
Other values (2) 2
 
2.9%
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 (%)
3 12
17.4%
1 12
17.4%
0 11
15.9%
2 8
11.6%
5 8
11.6%
, 4
 
5.8%
6 4
 
5.8%
4 4
 
5.8%
9 2
 
2.9%
8 2
 
2.9%
Other values (2) 2
 
2.9%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 18
Text

MISSING 

Distinct20
Distinct (%)60.6%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T10:15:57.060378image/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

Unique15 ?
Unique (%)45.5%

Sample

1st row지원1동
2nd row4,267
3rd row9,083
4th row21
5th row9
ValueCountFrequency (%)
0 8
24.2%
21 4
 
12.1%
9 2
 
6.1%
24 2
 
6.1%
30 2
 
6.1%
지원1동 1
 
3.0%
79 1
 
3.0%
39 1
 
3.0%
40 1
 
3.0%
25 1
 
3.0%
Other values (10) 10
30.3%
2024-02-10T10:15:57.981455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 14
20.9%
2 11
16.4%
1 7
10.4%
4 7
10.4%
9 6
9.0%
3 5
 
7.5%
, 4
 
6.0%
7 3
 
4.5%
5 3
 
4.5%
8 2
 
3.0%
Other values (4) 5
 
7.5%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 14
23.3%
2 11
18.3%
1 7
11.7%
4 7
11.7%
9 6
10.0%
3 5
 
8.3%
7 3
 
5.0%
5 3
 
5.0%
8 2
 
3.3%
6 2
 
3.3%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
0 14
21.9%
2 11
17.2%
1 7
10.9%
4 7
10.9%
9 6
9.4%
3 5
 
7.8%
, 4
 
6.2%
7 3
 
4.7%
5 3
 
4.7%
8 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 14
21.9%
2 11
17.2%
1 7
10.9%
4 7
10.9%
9 6
9.4%
3 5
 
7.8%
, 4
 
6.2%
7 3
 
4.7%
5 3
 
4.7%
8 2
 
3.1%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 19
Text

MISSING 

Distinct23
Distinct (%)69.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T10:15:58.386525image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.3636364
Min length1

Characters and Unicode

Total characters78
Distinct characters14
Distinct 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 row지원2동
2nd row7,956
3rd row17,297
4th row96
5th row7
ValueCountFrequency (%)
0 7
21.2%
7 3
 
9.1%
13 2
 
6.1%
86 2
 
6.1%
63 1
 
3.0%
96 1
 
3.0%
7,956 1
 
3.0%
17,677 1
 
3.0%
8,140 1
 
3.0%
1 1
 
3.0%
Other values (13) 13
39.4%
2024-02-10T10:15:59.180250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
7 14
17.9%
0 11
14.1%
1 8
10.3%
6 8
10.3%
3 6
7.7%
8 6
7.7%
9 6
7.7%
2 4
 
5.1%
5 4
 
5.1%
4 4
 
5.1%
Other values (4) 7
9.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 71
91.0%
Other Punctuation 4
 
5.1%
Other Letter 3
 
3.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
7 14
19.7%
0 11
15.5%
1 8
11.3%
6 8
11.3%
3 6
8.5%
8 6
8.5%
9 6
8.5%
2 4
 
5.6%
5 4
 
5.6%
4 4
 
5.6%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
7 14
18.7%
0 11
14.7%
1 8
10.7%
6 8
10.7%
3 6
8.0%
8 6
8.0%
9 6
8.0%
2 4
 
5.3%
5 4
 
5.3%
4 4
 
5.3%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
7 14
18.7%
0 11
14.7%
1 8
10.7%
6 8
10.7%
3 6
8.0%
8 6
8.0%
9 6
8.0%
2 4
 
5.3%
5 4
 
5.3%
4 4
 
5.3%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Correlations

2024-02-10T10:15:59.485887image/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: 20.0001.000NaNNaN0.9401.0001.0000.9251.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
Unnamed: 31.000NaN1.000NaN1.0001.0001.0001.0001.0001.0001.0000.8051.0001.0001.0001.0000.7900.790
Unnamed: 4NaNNaNNaN1.0001.0001.0001.0001.0001.0001.0001.0001.0000.0001.0001.0001.0001.0001.000
Unnamed: 51.0000.9401.0001.0001.0000.9870.9720.9880.9940.9880.9930.9850.9890.9900.9900.9720.9890.989
Unnamed: 61.0001.0001.0001.0000.9871.0000.9890.9850.9910.9880.9870.9850.9870.9950.9960.9910.9700.982
Unnamed: 71.0001.0001.0001.0000.9720.9891.0000.9830.9920.9920.9740.9880.9900.9950.9860.9970.9780.983
Unnamed: 81.0000.9251.0001.0000.9880.9850.9831.0000.9990.9951.0000.9850.9850.9740.9950.9901.0000.985
Unnamed: 91.0001.0001.0001.0000.9940.9910.9920.9991.0000.9951.0000.9850.9850.9870.9950.9941.0000.985
Unnamed: 101.0001.0001.0001.0000.9880.9880.9920.9950.9951.0000.9910.9940.9940.9910.9970.9950.9860.992
Unnamed: 111.0001.0001.0001.0000.9930.9870.9741.0001.0000.9911.0000.9870.9870.9851.0000.9841.0000.987
Unnamed: 131.0001.0000.8051.0000.9850.9850.9880.9850.9850.9940.9871.0000.9970.9931.0000.9890.9740.996
Unnamed: 141.0001.0001.0000.0000.9890.9870.9900.9850.9850.9940.9870.9971.0000.9951.0000.9920.9820.998
Unnamed: 151.0001.0001.0001.0000.9900.9950.9950.9740.9870.9910.9850.9930.9951.0000.9970.9860.9860.992
Unnamed: 161.0001.0001.0001.0000.9900.9960.9860.9950.9950.9971.0001.0001.0000.9971.0000.9911.0001.000
Unnamed: 171.0001.0001.0001.0000.9720.9910.9970.9900.9940.9950.9840.9890.9920.9860.9911.0000.9810.988
Unnamed: 181.0001.0000.7901.0000.9890.9700.9781.0001.0000.9861.0000.9740.9820.9861.0000.9811.0000.976
Unnamed: 191.0001.0000.7901.0000.9890.9820.9830.9850.9850.9920.9870.9960.9980.9921.0000.9880.9761.000

Missing values

2024-02-10T10:15:31.221879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-02-10T10:15:32.214868image/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.
2024-02-10T10:15:32.941841image/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>2024.01.03<NA><NA><NA><NA><NA><NA><NA>
1<NA>작성기준 :<NA>2023.11 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>55,1074,2532,4235,7205,6754,3424,678<NA>2,4562,3662,3163,4955,1604,2677,956
4<NA>전월말인구수<NA><NA><NA>106,9575,3613,68310,42113,3648,0289,871<NA>4,1304,2963,0297,33811,0569,08317,297
5<NA>전월말거주불명자수<NA><NA><NA>6343511976275324<NA>45135250232196
6<NA>전월말재외국민등록자수<NA><NA><NA>11367121167<NA>365102497
7<NA>증 가 요 인전 입<NA>1,51699481401448667<NA>644753757579539
8<NA><NA><NA>남자<NA>729402373704538<NA>322128343639250
9<NA><NA><NA>여자<NA>787592567744129<NA>322625413940289
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>46510200<NA>00370100
26<NA><NA>국외<NA><NA>0000000<NA>0000000
27<NA><NA>기타<NA><NA>0000000<NA>0000000
28<NA>세대수증감<NA><NA><NA>136-1-5-2564-5<NA>4-6-28-118184
29<NA>인구수증감<NA><NA><NA>208-15-12-5210-6-37<NA>1-23-23-3-3321380
30<NA>거주불명자수증감<NA><NA><NA>1-1170030<NA>-2-1-3514501
31<NA>금월말세대수<NA><NA><NA>55,2434,2522,4185,6955,6814,3464,673<NA>2,4602,3602,2883,4945,1614,2758,140
32<NA>금월말인구수<NA><NA><NA>107,1655,3463,67110,36913,3748,0229,834<NA>4,1314,2733,0067,33511,0239,10417,677
33<NA>금월말거주불명자수<NA><NA><NA>6353413676275624<NA>43121764282197
34<NA>금월말재외국민등록자수<NA><NA><NA>11366121167<NA>365102597

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