Overview

Dataset statistics

Number of variables20
Number of observations35
Missing cells193
Missing cells (%)27.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory5.6 KiB
Average record size in memory164.8 B

Variable types

Unsupported1
Text18
DateTime1

Dataset

Description2022-08-25
Author주민등록인구통계
URLhttps://bigdata.gwangju.go.kr/usr/dataSet/getDataDetailView.rd?dataSetUncd=DS000201926

Alerts

Unnamed: 12 has constant value ""Constant
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 10:05:09.991009
Analysis finished2024-02-10 10:05:16.506037
Duration6.52 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
2024-02-10T10:05:16.807828image/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%
2024-02-10T10:05:17.675529image/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
2024-02-10T10:05:18.116580image/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%
2024-02-10T10:05:19.006464image/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
2024-02-10T10:05:19.386309image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length9
Mean length3.4166667
Min length1

Characters and Unicode

Total characters41
Distinct characters20
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)16.7%

Sample

1st row광주광역시 동구
2nd row2022.07 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%
2022.07 1
7.1%
현재 1
7.1%
2024-02-10T10:05:20.266201image/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%
2 3
 
7.3%
계 2
 
4.9%
0 2
 
4.9%
여 2
 
4.9%
내 2
 
4.9%
간 2
 
4.9%
Other values (10) 12
29.3%

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 3
50.0%
0 2
33.3%
7 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 3
30.0%
0 2
20.0%
7 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 3
30.0%
0 2
20.0%
7 1
 
10.0%
. 1
 
10.0%

Unnamed: 4
Text

MISSING 

Distinct2
Distinct (%)50.0%
Missing31
Missing (%)88.6%
Memory size412.0 B
2024-02-10T10:05:20.617264image/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%
2024-02-10T10:05:21.486591image/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
2024-02-10T10:05:21.850631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length3.030303
Min length1

Characters and Unicode

Total characters100
Distinct characters15
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique24 ?
Unique (%)72.7%

Sample

1st row합 계
2nd row52,717
3rd row103,233
4th row873
5th row99
ValueCountFrequency (%)
0 3
 
8.8%
1 2
 
5.9%
3 2
 
5.9%
317 2
 
5.9%
394 1
 
2.9%
99 1
 
2.9%
1,383 1
 
2.9%
871 1
 
2.9%
103,432 1
 
2.9%
52,868 1
 
2.9%
Other values (19) 19
55.9%
2024-02-10T10:05:22.797432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 16
16.0%
3 14
14.0%
7 10
10.0%
5 10
10.0%
8 8
8.0%
9 8
8.0%
0 7
7.0%
6 6
 
6.0%
, 6
 
6.0%
2 5
 
5.0%
Other values (5) 10
10.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 89
89.0%
Other Punctuation 6
 
6.0%
Space Separator 2
 
2.0%
Other Letter 2
 
2.0%
Dash Punctuation 1
 
1.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 16
18.0%
3 14
15.7%
7 10
11.2%
5 10
11.2%
8 8
9.0%
9 8
9.0%
0 7
7.9%
6 6
 
6.7%
2 5
 
5.6%
4 5
 
5.6%
Other Letter
ValueCountFrequency (%)
합 1
50.0%
계 1
50.0%
Other Punctuation
ValueCountFrequency (%)
, 6
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 98
98.0%
Hangul 2
 
2.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 16
16.3%
3 14
14.3%
7 10
10.2%
5 10
10.2%
8 8
8.2%
9 8
8.2%
0 7
7.1%
6 6
 
6.1%
, 6
 
6.1%
2 5
 
5.1%
Other values (3) 8
8.2%
Hangul
ValueCountFrequency (%)
합 1
50.0%
계 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 98
98.0%
Hangul 2
 
2.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 16
16.3%
3 14
14.3%
7 10
10.2%
5 10
10.2%
8 8
8.2%
9 8
8.2%
0 7
7.1%
6 6
 
6.1%
, 6
 
6.1%
2 5
 
5.1%
Other values (3) 8
8.2%
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
2024-02-10T10:05:23.294213image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
Mean length2.0909091
Min length1

Characters and Unicode

Total characters69
Distinct characters15
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique19 ?
Unique (%)57.6%

Sample

1st row충장동
2nd row3,762
3rd row4,866
4th row84
5th row7
ValueCountFrequency (%)
0 8
24.2%
49 2
 
6.1%
7 2
 
6.1%
42 2
 
6.1%
3,762 1
 
3.0%
84 1
 
3.0%
37 1
 
3.0%
4,915 1
 
3.0%
3,804 1
 
3.0%
1 1
 
3.0%
Other values (13) 13
39.4%
2024-02-10T10:05:24.143135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4 12
17.4%
0 9
13.0%
2 6
8.7%
7 6
8.7%
3 6
8.7%
9 5
7.2%
8 5
7.2%
6 5
7.2%
, 4
 
5.8%
1 4
 
5.8%
Other values (5) 7
10.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 61
88.4%
Other Punctuation 4
 
5.8%
Other Letter 3
 
4.3%
Dash Punctuation 1
 
1.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 12
19.7%
0 9
14.8%
2 6
9.8%
7 6
9.8%
3 6
9.8%
9 5
8.2%
8 5
8.2%
6 5
8.2%
1 4
 
6.6%
5 3
 
4.9%
Other Letter
ValueCountFrequency (%)
충 1
33.3%
장 1
33.3%
동 1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
4 12
18.2%
0 9
13.6%
2 6
9.1%
7 6
9.1%
3 6
9.1%
9 5
7.6%
8 5
7.6%
6 5
7.6%
, 4
 
6.1%
1 4
 
6.1%
Other values (2) 4
 
6.1%
Hangul
ValueCountFrequency (%)
충 1
33.3%
장 1
33.3%
동 1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
4 12
18.2%
0 9
13.6%
2 6
9.1%
7 6
9.1%
3 6
9.1%
9 5
7.6%
8 5
7.6%
6 5
7.6%
, 4
 
6.1%
1 4
 
6.1%
Other values (2) 4
 
6.1%
Hangul
ValueCountFrequency (%)
충 1
33.3%
장 1
33.3%
동 1
33.3%

Unnamed: 7
Text

MISSING 

Distinct20
Distinct (%)60.6%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T10:05:24.517801image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
Mean length2.0909091
Min length1

Characters and Unicode

Total characters69
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

Unique15 ?
Unique (%)45.5%

Sample

1st row동명동
2nd row2,463
3rd row3,845
4th row112
5th row6
ValueCountFrequency (%)
0 8
24.2%
6 3
 
9.1%
11 3
 
9.1%
112 2
 
6.1%
28 2
 
6.1%
16 1
 
3.0%
52 1
 
3.0%
2,474 1
 
3.0%
1 1
 
3.0%
21 1
 
3.0%
Other values (10) 10
30.3%
2024-02-10T10:05:25.401538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 15
21.7%
2 10
14.5%
0 9
13.0%
6 6
 
8.7%
8 6
 
8.7%
4 5
 
7.2%
5 5
 
7.2%
, 4
 
5.8%
3 4
 
5.8%
동 2
 
2.9%
Other values (3) 3
 
4.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 62
89.9%
Other Punctuation 4
 
5.8%
Other Letter 3
 
4.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 15
24.2%
2 10
16.1%
0 9
14.5%
6 6
 
9.7%
8 6
 
9.7%
4 5
 
8.1%
5 5
 
8.1%
3 4
 
6.5%
9 1
 
1.6%
7 1
 
1.6%
Other Letter
ValueCountFrequency (%)
동 2
66.7%
명 1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
1 15
22.7%
2 10
15.2%
0 9
13.6%
6 6
 
9.1%
8 6
 
9.1%
4 5
 
7.6%
5 5
 
7.6%
, 4
 
6.1%
3 4
 
6.1%
9 1
 
1.5%
Hangul
ValueCountFrequency (%)
동 2
66.7%
명 1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 15
22.7%
2 10
15.2%
0 9
13.6%
6 6
 
9.1%
8 6
 
9.1%
4 5
 
7.6%
5 5
 
7.6%
, 4
 
6.1%
3 4
 
6.1%
9 1
 
1.5%
Hangul
ValueCountFrequency (%)
동 2
66.7%
명 1
33.3%

Unnamed: 8
Text

MISSING 

Distinct26
Distinct (%)78.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T10:05:25.758300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length2
Mean length2.2121212
Min length1

Characters and Unicode

Total characters73
Distinct characters15
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique24 ?
Unique (%)72.7%

Sample

1st row계림1동
2nd row5,937
3rd row10,847
4th row94
5th row12
ValueCountFrequency (%)
0 7
21.2%
12 2
 
6.1%
94 2
 
6.1%
8 1
 
3.0%
44 1
 
3.0%
10,844 1
 
3.0%
5,925 1
 
3.0%
3 1
 
3.0%
1 1
 
3.0%
2 1
 
3.0%
Other values (15) 15
45.5%
2024-02-10T10:05:26.631663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 11
15.1%
1 11
15.1%
4 10
13.7%
9 7
9.6%
5 6
8.2%
3 5
6.8%
8 5
6.8%
2 5
6.8%
, 4
 
5.5%
7 2
 
2.7%
Other values (5) 7
9.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 64
87.7%
Other Punctuation 4
 
5.5%
Other Letter 3
 
4.1%
Dash Punctuation 2
 
2.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 11
17.2%
1 11
17.2%
4 10
15.6%
9 7
10.9%
5 6
9.4%
3 5
7.8%
8 5
7.8%
2 5
7.8%
7 2
 
3.1%
6 2
 
3.1%
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 70
95.9%
Hangul 3
 
4.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 11
15.7%
1 11
15.7%
4 10
14.3%
9 7
10.0%
5 6
8.6%
3 5
7.1%
8 5
7.1%
2 5
7.1%
, 4
 
5.7%
7 2
 
2.9%
Other values (2) 4
 
5.7%
Hangul
ValueCountFrequency (%)
계 1
33.3%
림 1
33.3%
동 1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 11
15.7%
1 11
15.7%
4 10
14.3%
9 7
10.0%
5 6
8.6%
3 5
7.1%
8 5
7.1%
2 5
7.1%
, 4
 
5.7%
7 2
 
2.9%
Other values (2) 4
 
5.7%
Hangul
ValueCountFrequency (%)
계 1
33.3%
림 1
33.3%
동 1
33.3%

Unnamed: 9
Text

MISSING 

Distinct23
Distinct (%)69.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T10:05:27.034605image/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 row계림2동
2nd row4,148
3rd row9,742
4th row44
5th row12
ValueCountFrequency (%)
0 8
24.2%
44 3
 
9.1%
12 2
 
6.1%
46 1
 
3.0%
9,742 1
 
3.0%
4,148 1
 
3.0%
4,149 1
 
3.0%
36 1
 
3.0%
1 1
 
3.0%
2 1
 
3.0%
Other values (13) 13
39.4%
2024-02-10T10:05:28.291029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4 12
17.4%
0 11
15.9%
1 9
13.0%
2 9
13.0%
9 5
7.2%
6 5
7.2%
3 4
 
5.8%
, 4
 
5.8%
7 3
 
4.3%
5 2
 
2.9%
Other values (5) 5
7.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 61
88.4%
Other Punctuation 4
 
5.8%
Other Letter 3
 
4.3%
Dash Punctuation 1
 
1.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 12
19.7%
0 11
18.0%
1 9
14.8%
2 9
14.8%
9 5
8.2%
6 5
8.2%
3 4
 
6.6%
7 3
 
4.9%
5 2
 
3.3%
8 1
 
1.6%
Other Letter
ValueCountFrequency (%)
계 1
33.3%
림 1
33.3%
동 1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
4 12
18.2%
0 11
16.7%
1 9
13.6%
2 9
13.6%
9 5
7.6%
6 5
7.6%
3 4
 
6.1%
, 4
 
6.1%
7 3
 
4.5%
5 2
 
3.0%
Other values (2) 2
 
3.0%
Hangul
ValueCountFrequency (%)
계 1
33.3%
림 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 (%)
4 12
18.2%
0 11
16.7%
1 9
13.6%
2 9
13.6%
9 5
7.6%
6 5
7.6%
3 4
 
6.1%
, 4
 
6.1%
7 3
 
4.5%
5 2
 
3.0%
Other values (2) 2
 
3.0%
Hangul
ValueCountFrequency (%)
계 1
33.3%
림 1
33.3%
동 1
33.3%

Unnamed: 10
Text

MISSING 

Distinct23
Distinct (%)67.6%
Missing1
Missing (%)2.9%
Memory size412.0 B
2024-02-10T10:05:28.907732image/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

Unique18 ?
Unique (%)52.9%

Sample

1st row출력일자 :
2nd row산수1동
3rd row4,461
4th row8,471
5th row65
ValueCountFrequency (%)
0 8
22.9%
41 2
 
5.7%
47 2
 
5.7%
65 2
 
5.7%
6 2
 
5.7%
출력일자 1
 
2.9%
96 1
 
2.9%
4,458 1
 
2.9%
19 1
 
2.9%
3 1
 
2.9%
Other values (14) 14
40.0%
2024-02-10T10:05:30.229163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4 13
17.3%
1 9
12.0%
0 8
10.7%
6 7
9.3%
8 5
 
6.7%
5 4
 
5.3%
, 4
 
5.3%
7 4
 
5.3%
3 4
 
5.3%
2 3
 
4.0%
Other values (11) 14
18.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 60
80.0%
Other Letter 7
 
9.3%
Other Punctuation 5
 
6.7%
Dash Punctuation 2
 
2.7%
Space Separator 1
 
1.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 13
21.7%
1 9
15.0%
0 8
13.3%
6 7
11.7%
8 5
 
8.3%
5 4
 
6.7%
7 4
 
6.7%
3 4
 
6.7%
2 3
 
5.0%
9 3
 
5.0%
Other Letter
ValueCountFrequency (%)
산 1
14.3%
수 1
14.3%
동 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%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
4 13
19.1%
1 9
13.2%
0 8
11.8%
6 7
10.3%
8 5
 
7.4%
5 4
 
5.9%
, 4
 
5.9%
7 4
 
5.9%
3 4
 
5.9%
2 3
 
4.4%
Other values (4) 7
10.3%
Hangul
ValueCountFrequency (%)
산 1
14.3%
수 1
14.3%
동 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 (%)
4 13
19.1%
1 9
13.2%
0 8
11.8%
6 7
10.3%
8 5
 
7.4%
5 4
 
5.9%
, 4
 
5.9%
7 4
 
5.9%
3 4
 
5.9%
2 3
 
4.4%
Other values (4) 7
10.3%
Hangul
ValueCountFrequency (%)
산 1
14.3%
수 1
14.3%
동 1
14.3%
출 1
14.3%
력 1
14.3%
일 1
14.3%
자 1
14.3%

Unnamed: 11
Text

MISSING 

Distinct21
Distinct (%)63.6%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T10:05:30.723454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
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

Unique16 ?
Unique (%)48.5%

Sample

1st row산수2동
2nd row4,887
3rd row10,464
4th row37
5th row6
ValueCountFrequency (%)
0 8
24.2%
49 3
 
9.1%
6 2
 
6.1%
5 2
 
6.1%
37 2
 
6.1%
98 1
 
3.0%
10,464 1
 
3.0%
4,868 1
 
3.0%
38 1
 
3.0%
19 1
 
3.0%
Other values (11) 11
33.3%
2024-02-10T10:05:31.846036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 10
14.1%
4 10
14.1%
3 7
9.9%
8 7
9.9%
6 6
8.5%
9 5
7.0%
2 5
7.0%
1 5
7.0%
5 4
 
5.6%
, 4
 
5.6%
Other values (5) 8
11.3%

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 (%)
0 10
16.1%
4 10
16.1%
3 7
11.3%
8 7
11.3%
6 6
9.7%
9 5
8.1%
2 5
8.1%
1 5
8.1%
5 4
 
6.5%
7 3
 
4.8%
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 68
95.8%
Hangul 3
 
4.2%

Most frequent character per script

Common
ValueCountFrequency (%)
0 10
14.7%
4 10
14.7%
3 7
10.3%
8 7
10.3%
6 6
8.8%
9 5
7.4%
2 5
7.4%
1 5
7.4%
5 4
 
5.9%
, 4
 
5.9%
Other values (2) 5
7.4%
Hangul
ValueCountFrequency (%)
산 1
33.3%
수 1
33.3%
동 1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 10
14.7%
4 10
14.7%
3 7
10.3%
8 7
10.3%
6 6
8.8%
9 5
7.4%
2 5
7.4%
1 5
7.4%
5 4
 
5.9%
, 4
 
5.9%
Other values (2) 5
7.4%
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
Minimum2022-08-11 00:00:00
Maximum2022-08-11 00:00:00
2024-02-10T10:05:32.243478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-10T10:05:32.669833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Unnamed: 13
Text

MISSING 

Distinct22
Distinct (%)66.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T10:05:33.073362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length2
Min length1

Characters and Unicode

Total characters66
Distinct characters11
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 row2,425
3rd row4,210
4th row43
5th row2
ValueCountFrequency (%)
0 6
18.2%
1 3
 
9.1%
3 2
 
6.1%
43 2
 
6.1%
2 2
 
6.1%
23 2
 
6.1%
지산1동 1
 
3.0%
2,430 1
 
3.0%
5 1
 
3.0%
13 1
 
3.0%
Other values (12) 12
36.4%
2024-02-10T10:05:34.169436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 14
21.2%
1 11
16.7%
0 10
15.2%
3 9
13.6%
4 9
13.6%
, 4
 
6.1%
5 3
 
4.5%
6 3
 
4.5%
지 1
 
1.5%
산 1
 
1.5%

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 14
23.7%
1 11
18.6%
0 10
16.9%
3 9
15.3%
4 9
15.3%
5 3
 
5.1%
6 3
 
5.1%
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 63
95.5%
Hangul 3
 
4.5%

Most frequent character per script

Common
ValueCountFrequency (%)
2 14
22.2%
1 11
17.5%
0 10
15.9%
3 9
14.3%
4 9
14.3%
, 4
 
6.3%
5 3
 
4.8%
6 3
 
4.8%
Hangul
ValueCountFrequency (%)
지 1
33.3%
산 1
33.3%
동 1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 14
22.2%
1 11
17.5%
0 10
15.9%
3 9
14.3%
4 9
14.3%
, 4
 
6.3%
5 3
 
4.8%
6 3
 
4.8%
Hangul
ValueCountFrequency (%)
지 1
33.3%
산 1
33.3%
동 1
33.3%

Unnamed: 14
Text

MISSING 

Distinct24
Distinct (%)72.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T10:05:34.498222image/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 row지산2동
2nd row2,410
3rd row4,464
4th row41
5th row7
ValueCountFrequency (%)
0 8
24.2%
16 2
 
6.1%
41 2
 
6.1%
34 2
 
6.1%
25 1
 
3.0%
38 1
 
3.0%
4,430 1
 
3.0%
2,389 1
 
3.0%
21 1
 
3.0%
2 1
 
3.0%
Other values (13) 13
39.4%
2024-02-10T10:05:35.471856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4 14
20.0%
0 11
15.7%
2 10
14.3%
1 9
12.9%
3 6
8.6%
6 5
 
7.1%
, 4
 
5.7%
7 2
 
2.9%
- 2
 
2.9%
8 2
 
2.9%
Other values (5) 5
 
7.1%

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 (%)
4 14
23.0%
0 11
18.0%
2 10
16.4%
1 9
14.8%
3 6
9.8%
6 5
 
8.2%
7 2
 
3.3%
8 2
 
3.3%
5 1
 
1.6%
9 1
 
1.6%
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 67
95.7%
Hangul 3
 
4.3%

Most frequent character per script

Common
ValueCountFrequency (%)
4 14
20.9%
0 11
16.4%
2 10
14.9%
1 9
13.4%
3 6
9.0%
6 5
 
7.5%
, 4
 
6.0%
7 2
 
3.0%
- 2
 
3.0%
8 2
 
3.0%
Other values (2) 2
 
3.0%
Hangul
ValueCountFrequency (%)
지 1
33.3%
산 1
33.3%
동 1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
4 14
20.9%
0 11
16.4%
2 10
14.9%
1 9
13.4%
3 6
9.0%
6 5
 
7.5%
, 4
 
6.0%
7 2
 
3.0%
- 2
 
3.0%
8 2
 
3.0%
Other values (2) 2
 
3.0%
Hangul
ValueCountFrequency (%)
지 1
33.3%
산 1
33.3%
동 1
33.3%

Unnamed: 15
Text

MISSING 

Distinct24
Distinct (%)72.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T10:05:35.798126image/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

Unique21 ?
Unique (%)63.6%

Sample

1st row서남동
2nd row2,263
3rd row3,032
4th row63
5th row3
ValueCountFrequency (%)
0 8
24.2%
3 2
 
6.1%
26 2
 
6.1%
11 1
 
3.0%
63 1
 
3.0%
24 1
 
3.0%
3,048 1
 
3.0%
2,280 1
 
3.0%
1 1
 
3.0%
16 1
 
3.0%
Other values (14) 14
42.4%
2024-02-10T10:05:36.682822image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 12
17.9%
2 12
17.9%
3 10
14.9%
6 7
10.4%
1 6
9.0%
7 4
 
6.0%
, 4
 
6.0%
4 4
 
6.0%
8 2
 
3.0%
5 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 12
20.3%
2 12
20.3%
3 10
16.9%
6 7
11.9%
1 6
10.2%
7 4
 
6.8%
4 4
 
6.8%
8 2
 
3.4%
5 1
 
1.7%
9 1
 
1.7%
Other Letter
ValueCountFrequency (%)
서 1
33.3%
남 1
33.3%
동 1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
0 12
18.8%
2 12
18.8%
3 10
15.6%
6 7
10.9%
1 6
9.4%
7 4
 
6.2%
, 4
 
6.2%
4 4
 
6.2%
8 2
 
3.1%
5 1
 
1.6%
Other values (2) 2
 
3.1%
Hangul
ValueCountFrequency (%)
서 1
33.3%
남 1
33.3%
동 1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 12
18.8%
2 12
18.8%
3 10
15.6%
6 7
10.9%
1 6
9.4%
7 4
 
6.2%
, 4
 
6.2%
4 4
 
6.2%
8 2
 
3.1%
5 1
 
1.6%
Other values (2) 2
 
3.1%
Hangul
ValueCountFrequency (%)
서 1
33.3%
남 1
33.3%
동 1
33.3%

Unnamed: 16
Text

MISSING 

Distinct23
Distinct (%)69.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T10:05:37.116589image/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 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 row학동
2nd row3,619
3rd row7,662
4th row77
5th row9
ValueCountFrequency (%)
0 8
24.2%
9 2
 
6.1%
29 2
 
6.1%
26 2
 
6.1%
77 2
 
6.1%
36 1
 
3.0%
42 1
 
3.0%
3,614 1
 
3.0%
5 1
 
3.0%
3 1
 
3.0%
Other values (12) 12
36.4%
2024-02-10T10:05:37.998134image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

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

Most occurring categories

ValueCountFrequency (%)
Decimal Number 59
88.1%
Other Punctuation 4
 
6.0%
Dash Punctuation 2
 
3.0%
Other Letter 2
 
3.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
6 11
18.6%
0 8
13.6%
2 8
13.6%
7 7
11.9%
3 6
10.2%
9 5
8.5%
4 5
8.5%
1 4
 
6.8%
5 3
 
5.1%
8 2
 
3.4%
Other Letter
ValueCountFrequency (%)
학 1
50.0%
동 1
50.0%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 65
97.0%
Hangul 2
 
3.0%

Most frequent character per script

Common
ValueCountFrequency (%)
6 11
16.9%
0 8
12.3%
2 8
12.3%
7 7
10.8%
3 6
9.2%
9 5
7.7%
4 5
7.7%
, 4
 
6.2%
1 4
 
6.2%
5 3
 
4.6%
Other values (2) 4
 
6.2%
Hangul
ValueCountFrequency (%)
학 1
50.0%
동 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 65
97.0%
Hangul 2
 
3.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6 11
16.9%
0 8
12.3%
2 8
12.3%
7 7
10.8%
3 6
9.2%
9 5
7.7%
4 5
7.7%
, 4
 
6.2%
1 4
 
6.2%
5 3
 
4.6%
Other values (2) 4
 
6.2%
Hangul
ValueCountFrequency (%)
학 1
50.0%
동 1
50.0%

Unnamed: 17
Text

MISSING 

Distinct21
Distinct (%)63.6%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T10:05:38.371968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.2424242
Min length1

Characters and Unicode

Total characters74
Distinct characters15
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique16 ?
Unique (%)48.5%

Sample

1st row학운동
2nd row5,250
3rd row11,322
4th row65
5th row14
ValueCountFrequency (%)
0 8
24.2%
36 3
 
9.1%
65 2
 
6.1%
14 2
 
6.1%
48 2
 
6.1%
32 1
 
3.0%
120 1
 
3.0%
5,239 1
 
3.0%
39 1
 
3.0%
11 1
 
3.0%
Other values (11) 11
33.3%
2024-02-10T10:05:39.489893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 10
13.5%
3 10
13.5%
1 10
13.5%
2 8
10.8%
5 7
9.5%
6 6
8.1%
4 5
6.8%
8 4
 
5.4%
, 4
 
5.4%
9 4
 
5.4%
Other values (5) 6
8.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 65
87.8%
Other Punctuation 4
 
5.4%
Other Letter 3
 
4.1%
Dash Punctuation 2
 
2.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 10
15.4%
3 10
15.4%
1 10
15.4%
2 8
12.3%
5 7
10.8%
6 6
9.2%
4 5
7.7%
8 4
 
6.2%
9 4
 
6.2%
7 1
 
1.5%
Other Letter
ValueCountFrequency (%)
학 1
33.3%
운 1
33.3%
동 1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
0 10
14.1%
3 10
14.1%
1 10
14.1%
2 8
11.3%
5 7
9.9%
6 6
8.5%
4 5
7.0%
8 4
 
5.6%
, 4
 
5.6%
9 4
 
5.6%
Other values (2) 3
 
4.2%
Hangul
ValueCountFrequency (%)
학 1
33.3%
운 1
33.3%
동 1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 10
14.1%
3 10
14.1%
1 10
14.1%
2 8
11.3%
5 7
9.9%
6 6
8.5%
4 5
7.0%
8 4
 
5.6%
, 4
 
5.6%
9 4
 
5.6%
Other values (2) 3
 
4.2%
Hangul
ValueCountFrequency (%)
학 1
33.3%
운 1
33.3%
동 1
33.3%

Unnamed: 18
Text

MISSING 

Distinct24
Distinct (%)72.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T10:05:39.882838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
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

Unique22 ?
Unique (%)66.7%

Sample

1st row지원1동
2nd row3,912
3rd row8,328
4th row23
5th row7
ValueCountFrequency (%)
0 8
24.2%
23 3
 
9.1%
8,328 1
 
3.0%
3,912 1
 
3.0%
8,711 1
 
3.0%
4,073 1
 
3.0%
383 1
 
3.0%
161 1
 
3.0%
5 1
 
3.0%
25 1
 
3.0%
Other values (14) 14
42.4%
2024-02-10T10:05:40.733878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 12
16.0%
2 11
14.7%
3 11
14.7%
0 9
12.0%
8 7
9.3%
5 6
8.0%
7 5
6.7%
4 4
 
5.3%
, 4
 
5.3%
6 2
 
2.7%
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 12
17.6%
2 11
16.2%
3 11
16.2%
0 9
13.2%
8 7
10.3%
5 6
8.8%
7 5
7.4%
4 4
 
5.9%
6 2
 
2.9%
9 1
 
1.5%
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 72
96.0%
Hangul 3
 
4.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 12
16.7%
2 11
15.3%
3 11
15.3%
0 9
12.5%
8 7
9.7%
5 6
8.3%
7 5
6.9%
4 4
 
5.6%
, 4
 
5.6%
6 2
 
2.8%
Hangul
ValueCountFrequency (%)
지 1
33.3%
원 1
33.3%
동 1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 12
16.7%
2 11
15.3%
3 11
15.3%
0 9
12.5%
8 7
9.7%
5 6
8.3%
7 5
6.9%
4 4
 
5.6%
, 4
 
5.6%
6 2
 
2.8%
Hangul
ValueCountFrequency (%)
지 1
33.3%
원 1
33.3%
동 1
33.3%

Unnamed: 19
Text

MISSING 

Distinct24
Distinct (%)72.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T10:05:41.061302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.3939394
Min length1

Characters and Unicode

Total characters79
Distinct characters14
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique20 ?
Unique (%)60.6%

Sample

1st row지원2동
2nd row7,180
3rd row15,980
4th row125
5th row8
ValueCountFrequency (%)
0 7
21.2%
8 2
 
6.1%
75 2
 
6.1%
125 2
 
6.1%
10 1
 
3.0%
104 1
 
3.0%
7,165 1
 
3.0%
68 1
 
3.0%
15 1
 
3.0%
6 1
 
3.0%
Other values (14) 14
42.4%
2024-02-10T10:05:41.920160image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 15
19.0%
0 14
17.7%
2 10
12.7%
5 9
11.4%
8 8
10.1%
7 4
 
5.1%
, 4
 
5.1%
6 4
 
5.1%
4 3
 
3.8%
9 3
 
3.8%
Other values (4) 5
 
6.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 70
88.6%
Other Punctuation 4
 
5.1%
Other Letter 3
 
3.8%
Dash Punctuation 2
 
2.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 15
21.4%
0 14
20.0%
2 10
14.3%
5 9
12.9%
8 8
11.4%
7 4
 
5.7%
6 4
 
5.7%
4 3
 
4.3%
9 3
 
4.3%
Other Letter
ValueCountFrequency (%)
지 1
33.3%
원 1
33.3%
동 1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 76
96.2%
Hangul 3
 
3.8%

Most frequent character per script

Common
ValueCountFrequency (%)
1 15
19.7%
0 14
18.4%
2 10
13.2%
5 9
11.8%
8 8
10.5%
7 4
 
5.3%
, 4
 
5.3%
6 4
 
5.3%
4 3
 
3.9%
9 3
 
3.9%
Hangul
ValueCountFrequency (%)
지 1
33.3%
원 1
33.3%
동 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 76
96.2%
Hangul 3
 
3.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 15
19.7%
0 14
18.4%
2 10
13.2%
5 9
11.8%
8 8
10.5%
7 4
 
5.3%
, 4
 
5.3%
6 4
 
5.3%
4 3
 
3.9%
9 3
 
3.9%
Hangul
ValueCountFrequency (%)
지 1
33.3%
원 1
33.3%
동 1
33.3%

Correlations

2024-02-10T10:05:42.150349image/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: 20.0001.000NaNNaN0.8651.0001.0001.0001.0001.0001.0000.8571.0001.0001.0001.0001.0001.000
Unnamed: 31.000NaN1.000NaN1.0001.0001.0001.0001.0001.0000.7900.7901.0001.0001.0000.7901.0000.790
Unnamed: 4NaNNaNNaN1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0000.0001.0001.000
Unnamed: 51.0000.8651.0001.0001.0000.9910.9930.9870.9910.9900.9940.9860.9840.9920.9910.9940.9920.984
Unnamed: 61.0001.0001.0001.0000.9911.0000.9860.9830.9950.9790.9740.9760.9750.9960.9930.9770.9750.975
Unnamed: 71.0001.0001.0001.0000.9930.9861.0001.0000.9930.9900.9790.9830.9890.9890.9950.9790.9960.995
Unnamed: 81.0001.0001.0001.0000.9870.9831.0001.0001.0001.0001.0000.9941.0000.9851.0001.0001.0000.994
Unnamed: 91.0001.0001.0001.0000.9910.9950.9931.0001.0000.9950.9930.9860.9870.9870.9990.9940.9960.995
Unnamed: 101.0001.0001.0001.0000.9900.9790.9901.0000.9951.0000.9910.9930.9880.9901.0000.9940.9960.996
Unnamed: 111.0001.0000.7901.0000.9940.9740.9791.0000.9930.9911.0000.9850.9840.9820.9900.9930.9970.989
Unnamed: 131.0000.8570.7901.0000.9860.9760.9830.9940.9860.9930.9851.0000.9860.9800.9830.9690.9890.983
Unnamed: 141.0001.0001.0001.0000.9840.9750.9891.0000.9870.9880.9840.9861.0000.9940.9900.9870.9970.993
Unnamed: 151.0001.0001.0001.0000.9920.9960.9890.9850.9870.9900.9820.9800.9941.0000.9900.9900.9930.993
Unnamed: 161.0001.0001.0001.0000.9910.9930.9951.0000.9991.0000.9900.9830.9900.9901.0000.9980.9950.996
Unnamed: 171.0001.0000.7900.0000.9940.9770.9791.0000.9940.9940.9930.9690.9870.9900.9981.0000.9940.996
Unnamed: 181.0001.0001.0001.0000.9920.9750.9961.0000.9960.9960.9970.9890.9970.9930.9950.9941.0000.997
Unnamed: 191.0001.0000.7901.0000.9840.9750.9950.9940.9950.9960.9890.9830.9930.9930.9960.9960.9971.000

Missing values

2024-02-10T10:05:14.266079image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-02-10T10:05:15.223932image/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.
2024-02-10T10:05:15.904793image/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>2022.08.11<NA><NA><NA><NA><NA><NA><NA>
1<NA>작성기준 :<NA>2022.07 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>52,7173,7622,4635,9374,1484,4614,887<NA>2,4252,4102,2633,6195,2503,9127,180
4<NA>전월말인구수<NA><NA><NA>103,2334,8663,84510,8479,7428,47110,464<NA>4,2104,4643,0327,66211,3228,32815,980
5<NA>전월말거주불명자수<NA><NA><NA>8738411294446537<NA>434163776523125
6<NA>전월말재외국민등록자수<NA><NA><NA>9976121266<NA>27391478
7<NA>증 가 요 인전 입계<NA>1,3831395891518362<NA>5044675789442150
8<NA><NA><NA>남자<NA>695753046214234<NA>262430285321175
9<NA><NA><NA>여자<NA>688642845304128<NA>242037293623175
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>3001000<NA>0200000
26<NA><NA>국외<NA><NA>0000000<NA>0000000
27<NA><NA>기타<NA><NA>1000000<NA>1000000
28<NA>세대수증감<NA><NA><NA>1514211-121-3-19<NA>5-2117-5-11161-15
29<NA>인구수증감<NA><NA><NA>1994911-3-36-19-38<NA>3-3416-26-39383-68
30<NA>거주불명자수증감<NA><NA><NA>-2-100000<NA>00-10000
31<NA>금월말세대수<NA><NA><NA>52,8683,8042,4745,9254,1494,4584,868<NA>2,4302,3892,2803,6145,2394,0737,165
32<NA>금월말인구수<NA><NA><NA>103,4324,9153,85610,8449,7068,45210,426<NA>4,2134,4303,0487,63611,2838,71115,912
33<NA>금월말거주불명자수<NA><NA><NA>8718311294446537<NA>434162776523125
34<NA>금월말재외국민등록자수<NA><NA><NA>10076131265<NA>36391488