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

Description2022-09-16
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 10:05:46.562326
Analysis finished2024-02-10 10:05:52.784555
Duration6.22 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
2024-02-10T10:05:52.996473image/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%
2024-02-10T10:05:54.056713image/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
2024-02-10T10:05:54.478289image/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%
2024-02-10T10:05:55.444278image/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
2024-02-10T10:05:55.869184image/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 row2022.08 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%
2022.08 1
7.1%
현재 1
7.1%
2024-02-10T10:05:56.735850image/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%
8 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%
8 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%
8 1
 
10.0%
. 1
 
10.0%

Unnamed: 4
Text

MISSING 

Distinct2
Distinct (%)50.0%
Missing31
Missing (%)88.6%
Memory size412.0 B
2024-02-10T10:05:57.212982image/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%
2024-02-10T10:05:57.788959image/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
2024-02-10T10:05:58.190343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length3.2727273
Min length1

Characters and Unicode

Total characters108
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

Unique26 ?
Unique (%)78.8%

Sample

1st row합 계
2nd row52,868
3rd row103,432
4th row871
5th row100
ValueCountFrequency (%)
0 5
 
14.7%
541 2
 
5.9%
746 1
 
2.9%
776 1
 
2.9%
875 1
 
2.9%
105,137 1
 
2.9%
53,722 1
 
2.9%
4 1
 
2.9%
1,705 1
 
2.9%
854 1
 
2.9%
Other values (19) 19
55.9%
2024-02-10T10:05:59.207512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 15
13.9%
0 14
13.0%
5 13
12.0%
2 11
10.2%
, 10
9.3%
7 10
9.3%
4 9
8.3%
8 8
7.4%
6 7
6.5%
3 5
 
4.6%
Other values (4) 6
 
5.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 94
87.0%
Other Punctuation 10
 
9.3%
Space Separator 2
 
1.9%
Other Letter 2
 
1.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 15
16.0%
0 14
14.9%
5 13
13.8%
2 11
11.7%
7 10
10.6%
4 9
9.6%
8 8
8.5%
6 7
7.4%
3 5
 
5.3%
9 2
 
2.1%
Other Letter
ValueCountFrequency (%)
합 1
50.0%
계 1
50.0%
Other Punctuation
ValueCountFrequency (%)
, 10
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 106
98.1%
Hangul 2
 
1.9%

Most frequent character per script

Common
ValueCountFrequency (%)
1 15
14.2%
0 14
13.2%
5 13
12.3%
2 11
10.4%
, 10
9.4%
7 10
9.4%
4 9
8.5%
8 8
7.5%
6 7
6.6%
3 5
 
4.7%
Other values (2) 4
 
3.8%
Hangul
ValueCountFrequency (%)
합 1
50.0%
계 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 106
98.1%
Hangul 2
 
1.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 15
14.2%
0 14
13.2%
5 13
12.3%
2 11
10.4%
, 10
9.4%
7 10
9.4%
4 9
8.5%
8 8
7.5%
6 7
6.6%
3 5
 
4.7%
Other values (2) 4
 
3.8%
Hangul
ValueCountFrequency (%)
합 1
50.0%
계 1
50.0%

Unnamed: 6
Text

MISSING 

Distinct24
Distinct (%)72.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T10:05:59.611371image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
Mean length2.1818182
Min length1

Characters and Unicode

Total characters72
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 row충장동
2nd row3,804
3rd row4,915
4th row83
5th row7
ValueCountFrequency (%)
0 8
24.2%
7 2
 
6.1%
2 2
 
6.1%
44 1
 
3.0%
83 1
 
3.0%
60 1
 
3.0%
5,009 1
 
3.0%
3,897 1
 
3.0%
94 1
 
3.0%
93 1
 
3.0%
Other values (14) 14
42.4%
2024-02-10T10:06:00.575245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 16
22.2%
2 8
11.1%
1 7
9.7%
7 6
 
8.3%
9 6
 
8.3%
3 6
 
8.3%
8 5
 
6.9%
4 5
 
6.9%
5 4
 
5.6%
, 4
 
5.6%
Other values (4) 5
 
6.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 65
90.3%
Other Punctuation 4
 
5.6%
Other Letter 3
 
4.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 16
24.6%
2 8
12.3%
1 7
10.8%
7 6
 
9.2%
9 6
 
9.2%
3 6
 
9.2%
8 5
 
7.7%
4 5
 
7.7%
5 4
 
6.2%
6 2
 
3.1%
Other Letter
ValueCountFrequency (%)
충 1
33.3%
장 1
33.3%
동 1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
0 16
23.2%
2 8
11.6%
1 7
10.1%
7 6
 
8.7%
9 6
 
8.7%
3 6
 
8.7%
8 5
 
7.2%
4 5
 
7.2%
5 4
 
5.8%
, 4
 
5.8%
Hangul
ValueCountFrequency (%)
충 1
33.3%
장 1
33.3%
동 1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 16
23.2%
2 8
11.6%
1 7
10.1%
7 6
 
8.7%
9 6
 
8.7%
3 6
 
8.7%
8 5
 
7.2%
4 5
 
7.2%
5 4
 
5.8%
, 4
 
5.8%
Hangul
ValueCountFrequency (%)
충 1
33.3%
장 1
33.3%
동 1
33.3%

Unnamed: 7
Text

MISSING 

Distinct22
Distinct (%)66.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T10:06:01.105724image/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

Unique17 ?
Unique (%)51.5%

Sample

1st row동명동
2nd row2,474
3rd row3,856
4th row112
5th row6
ValueCountFrequency (%)
0 8
24.2%
6 2
 
6.1%
41 2
 
6.1%
2 2
 
6.1%
112 2
 
6.1%
29 1
 
3.0%
80 1
 
3.0%
2,496 1
 
3.0%
12 1
 
3.0%
22 1
 
3.0%
Other values (12) 12
36.4%
2024-02-10T10:06:02.604111image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 13
18.8%
0 10
14.5%
1 9
13.0%
4 7
10.1%
6 6
8.7%
8 5
 
7.2%
, 4
 
5.8%
3 4
 
5.8%
9 4
 
5.8%
5 3
 
4.3%
Other values (3) 4
 
5.8%

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 (%)
2 13
21.0%
0 10
16.1%
1 9
14.5%
4 7
11.3%
6 6
9.7%
8 5
 
8.1%
3 4
 
6.5%
9 4
 
6.5%
5 3
 
4.8%
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 (%)
2 13
19.7%
0 10
15.2%
1 9
13.6%
4 7
10.6%
6 6
9.1%
8 5
 
7.6%
, 4
 
6.1%
3 4
 
6.1%
9 4
 
6.1%
5 3
 
4.5%
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 (%)
2 13
19.7%
0 10
15.2%
1 9
13.6%
4 7
10.6%
6 6
9.1%
8 5
 
7.6%
, 4
 
6.1%
3 4
 
6.1%
9 4
 
6.1%
5 3
 
4.5%
Hangul
ValueCountFrequency (%)
동 2
66.7%
명 1
33.3%

Unnamed: 8
Text

MISSING 

Distinct25
Distinct (%)75.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T10:06:03.108153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.3030303
Min length1

Characters and Unicode

Total characters76
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 row5,925
3rd row10,844
4th row94
5th row13
ValueCountFrequency (%)
0 7
21.2%
5 2
 
6.1%
28 2
 
6.1%
39 2
 
6.1%
90 1
 
3.0%
94 1
 
3.0%
13 1
 
3.0%
99 1
 
3.0%
10,755 1
 
3.0%
5,897 1
 
3.0%
Other values (14) 14
42.4%
2024-02-10T10:06:04.900008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 12
15.8%
5 12
15.8%
9 11
14.5%
1 10
13.2%
8 7
9.2%
, 4
 
5.3%
4 4
 
5.3%
3 3
 
3.9%
7 3
 
3.9%
2 3
 
3.9%
Other values (5) 7
9.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 67
88.2%
Other Punctuation 4
 
5.3%
Other Letter 3
 
3.9%
Dash Punctuation 2
 
2.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 12
17.9%
5 12
17.9%
9 11
16.4%
1 10
14.9%
8 7
10.4%
4 4
 
6.0%
3 3
 
4.5%
7 3
 
4.5%
2 3
 
4.5%
6 2
 
3.0%
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 73
96.1%
Hangul 3
 
3.9%

Most frequent character per script

Common
ValueCountFrequency (%)
0 12
16.4%
5 12
16.4%
9 11
15.1%
1 10
13.7%
8 7
9.6%
, 4
 
5.5%
4 4
 
5.5%
3 3
 
4.1%
7 3
 
4.1%
2 3
 
4.1%
Other values (2) 4
 
5.5%
Hangul
ValueCountFrequency (%)
계 1
33.3%
림 1
33.3%
동 1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 12
16.4%
5 12
16.4%
9 11
15.1%
1 10
13.7%
8 7
9.6%
, 4
 
5.5%
4 4
 
5.5%
3 3
 
4.1%
7 3
 
4.1%
2 3
 
4.1%
Other values (2) 4
 
5.5%
Hangul
ValueCountFrequency (%)
계 1
33.3%
림 1
33.3%
동 1
33.3%

Unnamed: 9
Text

MISSING 

Distinct27
Distinct (%)81.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T10:06:05.236717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.6060606
Min length1

Characters and Unicode

Total characters86
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 row계림2동
2nd row4,149
3rd row9,706
4th row44
5th row12
ValueCountFrequency (%)
0 6
 
18.2%
12 2
 
6.1%
1 2
 
6.1%
48 1
 
3.0%
11,486 1
 
3.0%
4,855 1
 
3.0%
1,780 1
 
3.0%
706 1
 
3.0%
4 1
 
3.0%
31 1
 
3.0%
Other values (16) 16
48.5%
2024-02-10T10:06:06.186470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 13
15.1%
4 11
12.8%
0 10
11.6%
5 8
9.3%
2 7
8.1%
, 7
8.1%
9 6
7.0%
8 6
7.0%
3 5
 
5.8%
6 5
 
5.8%
Other values (5) 8
9.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 75
87.2%
Other Punctuation 7
 
8.1%
Other Letter 3
 
3.5%
Dash Punctuation 1
 
1.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 13
17.3%
4 11
14.7%
0 10
13.3%
5 8
10.7%
2 7
9.3%
9 6
8.0%
8 6
8.0%
3 5
 
6.7%
6 5
 
6.7%
7 4
 
5.3%
Other Letter
ValueCountFrequency (%)
계 1
33.3%
림 1
33.3%
동 1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 7
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 83
96.5%
Hangul 3
 
3.5%

Most frequent character per script

Common
ValueCountFrequency (%)
1 13
15.7%
4 11
13.3%
0 10
12.0%
5 8
9.6%
2 7
8.4%
, 7
8.4%
9 6
7.2%
8 6
7.2%
3 5
 
6.0%
6 5
 
6.0%
Other values (2) 5
 
6.0%
Hangul
ValueCountFrequency (%)
계 1
33.3%
림 1
33.3%
동 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 83
96.5%
Hangul 3
 
3.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 13
15.7%
4 11
13.3%
0 10
12.0%
5 8
9.6%
2 7
8.4%
, 7
8.4%
9 6
7.2%
8 6
7.2%
3 5
 
6.0%
6 5
 
6.0%
Other values (2) 5
 
6.0%
Hangul
ValueCountFrequency (%)
계 1
33.3%
림 1
33.3%
동 1
33.3%

Unnamed: 10
Text

MISSING 

Distinct24
Distinct (%)70.6%
Missing1
Missing (%)2.9%
Memory size412.0 B
2024-02-10T10:06:06.517611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.2941176
Min length1

Characters and Unicode

Total characters78
Distinct characters21
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique19 ?
Unique (%)55.9%

Sample

1st row출력일자 :
2nd row산수1동
3rd row4,458
4th row8,452
5th row65
ValueCountFrequency (%)
0 7
20.0%
55 2
 
5.7%
1 2
 
5.7%
65 2
 
5.7%
6 2
 
5.7%
87 1
 
2.9%
1
 
2.9%
출력일자 1
 
2.9%
186 1
 
2.9%
4,440 1
 
2.9%
Other values (15) 15
42.9%
2024-02-10T10:06:07.677352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 11
14.1%
0 10
12.8%
4 9
11.5%
8 8
10.3%
1 8
10.3%
6 6
7.7%
9 5
6.4%
, 4
 
5.1%
3 3
 
3.8%
- 2
 
2.6%
Other values (11) 12
15.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 63
80.8%
Other Letter 7
 
9.0%
Other Punctuation 5
 
6.4%
Dash Punctuation 2
 
2.6%
Space Separator 1
 
1.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 11
17.5%
0 10
15.9%
4 9
14.3%
8 8
12.7%
1 8
12.7%
6 6
9.5%
9 5
7.9%
3 3
 
4.8%
2 2
 
3.2%
7 1
 
1.6%
Other Letter
ValueCountFrequency (%)
동 1
14.3%
산 1
14.3%
수 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 71
91.0%
Hangul 7
 
9.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 11
15.5%
0 10
14.1%
4 9
12.7%
8 8
11.3%
1 8
11.3%
6 6
8.5%
9 5
7.0%
, 4
 
5.6%
3 3
 
4.2%
- 2
 
2.8%
Other values (4) 5
7.0%
Hangul
ValueCountFrequency (%)
동 1
14.3%
산 1
14.3%
수 1
14.3%
출 1
14.3%
력 1
14.3%
일 1
14.3%
자 1
14.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 71
91.0%
Hangul 7
 
9.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 11
15.5%
0 10
14.1%
4 9
12.7%
8 8
11.3%
1 8
11.3%
6 6
8.5%
9 5
7.0%
, 4
 
5.6%
3 3
 
4.2%
- 2
 
2.8%
Other values (4) 5
7.0%
Hangul
ValueCountFrequency (%)
동 1
14.3%
산 1
14.3%
수 1
14.3%
출 1
14.3%
력 1
14.3%
일 1
14.3%
자 1
14.3%

Unnamed: 11
Text

MISSING 

Distinct28
Distinct (%)84.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T10:06:08.038989image/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

Unique27 ?
Unique (%)81.8%

Sample

1st row산수2동
2nd row4,868
3rd row10,426
4th row37
5th row5
ValueCountFrequency (%)
0 6
 
18.2%
1 2
 
6.1%
81 2
 
6.1%
167 1
 
3.0%
36 1
 
3.0%
10,345 1
 
3.0%
4,841 1
 
3.0%
27 1
 
3.0%
8 1
 
3.0%
41 1
 
3.0%
Other values (16) 16
48.5%
2024-02-10T10:06:08.869458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 11
14.9%
0 10
13.5%
4 7
9.5%
8 7
9.5%
6 7
9.5%
2 6
8.1%
3 5
6.8%
, 4
 
5.4%
7 4
 
5.4%
5 4
 
5.4%
Other values (5) 9
12.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 64
86.5%
Other Punctuation 4
 
5.4%
Dash Punctuation 3
 
4.1%
Other Letter 3
 
4.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 11
17.2%
0 10
15.6%
4 7
10.9%
8 7
10.9%
6 7
10.9%
2 6
9.4%
3 5
7.8%
7 4
 
6.2%
5 4
 
6.2%
9 3
 
4.7%
Other Letter
ValueCountFrequency (%)
산 1
33.3%
수 1
33.3%
동 1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
1 11
15.5%
0 10
14.1%
4 7
9.9%
8 7
9.9%
6 7
9.9%
2 6
8.5%
3 5
7.0%
, 4
 
5.6%
7 4
 
5.6%
5 4
 
5.6%
Other values (2) 6
8.5%
Hangul
ValueCountFrequency (%)
산 1
33.3%
수 1
33.3%
동 1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 11
15.5%
0 10
14.1%
4 7
9.9%
8 7
9.9%
6 7
9.9%
2 6
8.5%
3 5
7.0%
, 4
 
5.6%
7 4
 
5.6%
5 4
 
5.6%
Other values (2) 6
8.5%
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
Minimum2022-09-14 00:00:00
Maximum2022-09-14 00:00:00
2024-02-10T10:06:09.337954image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-10T10:06:09.742243image/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
2024-02-10T10:06:10.033254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length2.0606061
Min length1

Characters and Unicode

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

Unique

Unique19 ?
Unique (%)57.6%

Sample

1st row지산1동
2nd row2,430
3rd row4,213
4th row43
5th row3
ValueCountFrequency (%)
0 8
24.2%
43 4
 
12.1%
3 2
 
6.1%
5 2
 
6.1%
38 1
 
3.0%
1 1
 
3.0%
2,446 1
 
3.0%
16 1
 
3.0%
20 1
 
3.0%
28 1
 
3.0%
Other values (11) 11
33.3%
2024-02-10T10:06:10.922060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 13
19.1%
4 11
16.2%
3 11
16.2%
2 6
8.8%
8 6
8.8%
1 5
 
7.4%
, 4
 
5.9%
5 4
 
5.9%
6 3
 
4.4%
7 1
 
1.5%
Other values (4) 4
 
5.9%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 13
21.7%
4 11
18.3%
3 11
18.3%
2 6
10.0%
8 6
10.0%
1 5
 
8.3%
5 4
 
6.7%
6 3
 
5.0%
7 1
 
1.7%
Other Letter
ValueCountFrequency (%)
지 1
33.3%
산 1
33.3%
동 1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
0 13
20.0%
4 11
16.9%
3 11
16.9%
2 6
9.2%
8 6
9.2%
1 5
 
7.7%
, 4
 
6.2%
5 4
 
6.2%
6 3
 
4.6%
7 1
 
1.5%
Hangul
ValueCountFrequency (%)
지 1
33.3%
산 1
33.3%
동 1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 13
20.0%
4 11
16.9%
3 11
16.9%
2 6
9.2%
8 6
9.2%
1 5
 
7.7%
, 4
 
6.2%
5 4
 
6.2%
6 3
 
4.6%
7 1
 
1.5%
Hangul
ValueCountFrequency (%)
지 1
33.3%
산 1
33.3%
동 1
33.3%

Unnamed: 14
Text

MISSING 

Distinct22
Distinct (%)66.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T10:06:11.304941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length2.0606061
Min length1

Characters and Unicode

Total characters68
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

Unique17 ?
Unique (%)51.5%

Sample

1st row지산2동
2nd row2,389
3rd row4,430
4th row41
5th row6
ValueCountFrequency (%)
0 8
24.2%
6 2
 
6.1%
11 2
 
6.1%
14 2
 
6.1%
41 2
 
6.1%
22 1
 
3.0%
52 1
 
3.0%
2,403 1
 
3.0%
2 1
 
3.0%
16 1
 
3.0%
Other values (12) 12
36.4%
2024-02-10T10:06:12.317336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 12
17.6%
0 11
16.2%
4 11
16.2%
2 10
14.7%
3 7
10.3%
6 4
 
5.9%
, 4
 
5.9%
8 2
 
2.9%
5 2
 
2.9%
9 1
 
1.5%
Other values (4) 4
 
5.9%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 12
19.7%
0 11
18.0%
4 11
18.0%
2 10
16.4%
3 7
11.5%
6 4
 
6.6%
8 2
 
3.3%
5 2
 
3.3%
9 1
 
1.6%
7 1
 
1.6%
Other Letter
ValueCountFrequency (%)
지 1
33.3%
산 1
33.3%
동 1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
1 12
18.5%
0 11
16.9%
4 11
16.9%
2 10
15.4%
3 7
10.8%
6 4
 
6.2%
, 4
 
6.2%
8 2
 
3.1%
5 2
 
3.1%
9 1
 
1.5%
Hangul
ValueCountFrequency (%)
지 1
33.3%
산 1
33.3%
동 1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 12
18.5%
0 11
16.9%
4 11
16.9%
2 10
15.4%
3 7
10.8%
6 4
 
6.2%
, 4
 
6.2%
8 2
 
3.1%
5 2
 
3.1%
9 1
 
1.5%
Hangul
ValueCountFrequency (%)
지 1
33.3%
산 1
33.3%
동 1
33.3%

Unnamed: 15
Text

MISSING 

Distinct22
Distinct (%)66.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T10:06:12.727046image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
Mean length2
Min length1

Characters and Unicode

Total characters66
Distinct characters15
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique18 ?
Unique (%)54.5%

Sample

1st row서남동
2nd row2,280
3rd row3,048
4th row62
5th row3
ValueCountFrequency (%)
0 8
24.2%
3 3
 
9.1%
24 2
 
6.1%
9 2
 
6.1%
51 1
 
3.0%
67 1
 
3.0%
3,067 1
 
3.0%
2,304 1
 
3.0%
1 1
 
3.0%
19 1
 
3.0%
Other values (12) 12
36.4%
2024-02-10T10:06:13.624976image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 13
19.7%
3 10
15.2%
2 8
12.1%
9 6
9.1%
4 5
 
7.6%
, 4
 
6.1%
6 4
 
6.1%
1 4
 
6.1%
8 3
 
4.5%
5 3
 
4.5%
Other values (5) 6
9.1%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 13
22.4%
3 10
17.2%
2 8
13.8%
9 6
10.3%
4 5
 
8.6%
6 4
 
6.9%
1 4
 
6.9%
8 3
 
5.2%
5 3
 
5.2%
7 2
 
3.4%
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 63
95.5%
Hangul 3
 
4.5%

Most frequent character per script

Common
ValueCountFrequency (%)
0 13
20.6%
3 10
15.9%
2 8
12.7%
9 6
9.5%
4 5
 
7.9%
, 4
 
6.3%
6 4
 
6.3%
1 4
 
6.3%
8 3
 
4.8%
5 3
 
4.8%
Other values (2) 3
 
4.8%
Hangul
ValueCountFrequency (%)
서 1
33.3%
남 1
33.3%
동 1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 13
20.6%
3 10
15.9%
2 8
12.7%
9 6
9.5%
4 5
 
7.9%
, 4
 
6.3%
6 4
 
6.3%
1 4
 
6.3%
8 3
 
4.8%
5 3
 
4.8%
Other values (2) 3
 
4.8%
Hangul
ValueCountFrequency (%)
서 1
33.3%
남 1
33.3%
동 1
33.3%

Unnamed: 16
Text

MISSING 

Distinct22
Distinct (%)66.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T10:06:14.135897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
Mean length2
Min length1

Characters and Unicode

Total characters66
Distinct characters13
Distinct 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 row학동
2nd row3,614
3rd row7,636
4th row77
5th row9
ValueCountFrequency (%)
0 8
24.2%
77 2
 
6.1%
9 2
 
6.1%
1 2
 
6.1%
27 2
 
6.1%
3,614 2
 
6.1%
41 1
 
3.0%
96 1
 
3.0%
4 1
 
3.0%
24 1
 
3.0%
Other values (11) 11
33.3%
2024-02-10T10:06:15.131649image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 9
13.6%
7 9
13.6%
3 8
12.1%
1 8
12.1%
4 8
12.1%
6 6
9.1%
9 5
7.6%
, 4
6.1%
2 4
6.1%
5 2
 
3.0%
Other values (3) 3
 
4.5%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 9
15.3%
7 9
15.3%
3 8
13.6%
1 8
13.6%
4 8
13.6%
6 6
10.2%
9 5
8.5%
2 4
6.8%
5 2
 
3.4%
Other Letter
ValueCountFrequency (%)
학 1
50.0%
동 1
50.0%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
0 9
14.1%
7 9
14.1%
3 8
12.5%
1 8
12.5%
4 8
12.5%
6 6
9.4%
9 5
7.8%
, 4
6.2%
2 4
6.2%
5 2
 
3.1%
Hangul
ValueCountFrequency (%)
학 1
50.0%
동 1
50.0%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 9
14.1%
7 9
14.1%
3 8
12.5%
1 8
12.5%
4 8
12.5%
6 6
9.4%
9 5
7.8%
, 4
6.2%
2 4
6.2%
5 2
 
3.1%
Hangul
ValueCountFrequency (%)
학 1
50.0%
동 1
50.0%

Unnamed: 17
Text

MISSING 

Distinct24
Distinct (%)72.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T10:06:15.495687image/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

Unique20 ?
Unique (%)60.6%

Sample

1st row학운동
2nd row5,239
3rd row11,283
4th row65
5th row14
ValueCountFrequency (%)
0 7
21.2%
14 2
 
6.1%
65 2
 
6.1%
2 2
 
6.1%
41 1
 
3.0%
11,283 1
 
3.0%
88 1
 
3.0%
5,236 1
 
3.0%
9 1
 
3.0%
3 1
 
3.0%
Other values (14) 14
42.4%
2024-02-10T10:06:16.375444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 10
13.9%
1 10
13.9%
0 9
12.5%
3 7
9.7%
4 6
8.3%
5 6
8.3%
9 5
6.9%
6 4
 
5.6%
, 4
 
5.6%
7 3
 
4.2%
Other values (5) 8
11.1%

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 (%)
2 10
15.9%
1 10
15.9%
0 9
14.3%
3 7
11.1%
4 6
9.5%
5 6
9.5%
9 5
7.9%
6 4
 
6.3%
7 3
 
4.8%
8 3
 
4.8%
Other Letter
ValueCountFrequency (%)
학 1
33.3%
운 1
33.3%
동 1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
2 10
14.5%
1 10
14.5%
0 9
13.0%
3 7
10.1%
4 6
8.7%
5 6
8.7%
9 5
7.2%
6 4
 
5.8%
, 4
 
5.8%
7 3
 
4.3%
Other values (2) 5
7.2%
Hangul
ValueCountFrequency (%)
학 1
33.3%
운 1
33.3%
동 1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 10
14.5%
1 10
14.5%
0 9
13.0%
3 7
10.1%
4 6
8.7%
5 6
8.7%
9 5
7.2%
6 4
 
5.8%
, 4
 
5.8%
7 3
 
4.3%
Other values (2) 5
7.2%
Hangul
ValueCountFrequency (%)
학 1
33.3%
운 1
33.3%
동 1
33.3%

Unnamed: 18
Text

MISSING 

Distinct22
Distinct (%)66.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T10:06:16.766444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length2.2121212
Min length1

Characters and Unicode

Total characters73
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 row4,073
3rd row8,711
4th row23
5th row8
ValueCountFrequency (%)
0 8
24.2%
8 3
 
9.1%
23 2
 
6.1%
40 2
 
6.1%
46 1
 
3.0%
8,711 1
 
3.0%
272 1
 
3.0%
4,149 1
 
3.0%
183 1
 
3.0%
76 1
 
3.0%
Other values (12) 12
36.4%
2024-02-10T10:06:17.503956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 13
17.8%
8 8
11.0%
3 8
11.0%
4 8
11.0%
1 8
11.0%
2 7
9.6%
9 5
 
6.8%
7 5
 
6.8%
, 4
 
5.5%
6 3
 
4.1%
Other values (4) 4
 
5.5%

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 (%)
0 13
19.7%
8 8
12.1%
3 8
12.1%
4 8
12.1%
1 8
12.1%
2 7
10.6%
9 5
 
7.6%
7 5
 
7.6%
6 3
 
4.5%
5 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 70
95.9%
Hangul 3
 
4.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 13
18.6%
8 8
11.4%
3 8
11.4%
4 8
11.4%
1 8
11.4%
2 7
10.0%
9 5
 
7.1%
7 5
 
7.1%
, 4
 
5.7%
6 3
 
4.3%
Hangul
ValueCountFrequency (%)
지 1
33.3%
원 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 13
18.6%
8 8
11.4%
3 8
11.4%
4 8
11.4%
1 8
11.4%
2 7
10.0%
9 5
 
7.1%
7 5
 
7.1%
, 4
 
5.7%
6 3
 
4.3%
Hangul
ValueCountFrequency (%)
지 1
33.3%
원 1
33.3%
동 1
33.3%

Unnamed: 19
Text

MISSING 

Distinct25
Distinct (%)75.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T10:06:17.864516image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.3939394
Min length1

Characters and Unicode

Total characters79
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 row지원2동
2nd row7,165
3rd row15,912
4th row125
5th row8
ValueCountFrequency (%)
0 7
21.2%
8 2
 
6.1%
125 2
 
6.1%
10 1
 
3.0%
221 1
 
3.0%
15,813 1
 
3.0%
7,144 1
 
3.0%
99 1
 
3.0%
21 1
 
3.0%
57 1
 
3.0%
Other values (15) 15
45.5%
2024-02-10T10:06:18.757207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 19
24.1%
0 9
11.4%
5 8
10.1%
2 7
 
8.9%
8 7
 
8.9%
7 5
 
6.3%
, 4
 
5.1%
9 4
 
5.1%
4 4
 
5.1%
3 4
 
5.1%
Other values (5) 8
10.1%

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 19
27.1%
0 9
12.9%
5 8
11.4%
2 7
 
10.0%
8 7
 
10.0%
7 5
 
7.1%
9 4
 
5.7%
4 4
 
5.7%
3 4
 
5.7%
6 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 19
25.0%
0 9
11.8%
5 8
10.5%
2 7
 
9.2%
8 7
 
9.2%
7 5
 
6.6%
, 4
 
5.3%
9 4
 
5.3%
4 4
 
5.3%
3 4
 
5.3%
Other values (2) 5
 
6.6%
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 19
25.0%
0 9
11.8%
5 8
10.5%
2 7
 
9.2%
8 7
 
9.2%
7 5
 
6.6%
, 4
 
5.3%
9 4
 
5.3%
4 4
 
5.3%
3 4
 
5.3%
Other values (2) 5
 
6.6%
Hangul
ValueCountFrequency (%)
지 1
33.3%
원 1
33.3%
동 1
33.3%

Correlations

2024-02-10T10:06:19.056234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
인구이동보고서(1호)Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 6Unnamed: 7Unnamed: 8Unnamed: 9Unnamed: 10Unnamed: 11Unnamed: 13Unnamed: 14Unnamed: 15Unnamed: 16Unnamed: 17Unnamed: 18Unnamed: 19
인구이동보고서(1호)1.0000.0001.000NaN1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
Unnamed: 20.0001.000NaNNaN1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
Unnamed: 31.000NaN1.000NaN1.0001.0000.7900.7901.0001.0001.0000.7901.0001.0001.0001.0000.7901.000
Unnamed: 4NaNNaNNaN1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
Unnamed: 51.0001.0001.0001.0001.0000.9920.9900.9920.9940.9910.9990.9900.9961.0000.9900.9920.9900.992
Unnamed: 61.0001.0001.0001.0000.9921.0000.9950.9931.0000.9911.0000.9900.9900.9960.9900.9990.9920.987
Unnamed: 71.0001.0000.7901.0000.9900.9951.0000.9931.0000.9931.0000.9980.9980.9920.9970.9980.9990.997
Unnamed: 81.0001.0000.7901.0000.9920.9930.9931.0000.9940.9861.0000.9880.9880.9910.9850.9880.9880.995
Unnamed: 91.0001.0001.0001.0000.9941.0001.0000.9941.0000.9960.9941.0001.0001.0001.0000.9971.0000.987
Unnamed: 101.0001.0001.0001.0000.9910.9910.9930.9860.9961.0001.0000.9910.9910.9760.9891.0000.9910.996
Unnamed: 111.0001.0001.0001.0000.9991.0001.0001.0000.9941.0001.0001.0001.0001.0000.9951.0001.0001.000
Unnamed: 131.0001.0000.7901.0000.9900.9900.9980.9881.0000.9911.0001.0000.9980.9870.9960.9970.9980.995
Unnamed: 141.0001.0001.0001.0000.9960.9900.9980.9881.0000.9911.0000.9981.0000.9920.9970.9970.9980.995
Unnamed: 151.0001.0001.0001.0001.0000.9960.9920.9911.0000.9761.0000.9870.9921.0000.9910.9860.9940.983
Unnamed: 161.0001.0001.0001.0000.9900.9900.9970.9851.0000.9890.9950.9960.9970.9911.0000.9950.9960.991
Unnamed: 171.0001.0001.0001.0000.9920.9990.9980.9880.9971.0001.0000.9970.9970.9860.9951.0000.9970.996
Unnamed: 181.0001.0000.7901.0000.9900.9920.9990.9881.0000.9911.0000.9980.9980.9940.9960.9971.0001.000
Unnamed: 191.0001.0001.0001.0000.9920.9870.9970.9950.9870.9961.0000.9950.9950.9830.9910.9961.0001.000

Missing values

2024-02-10T10:05:50.389093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-02-10T10:05:51.294010image/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.
2024-02-10T10:05:52.014047image/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>2022.09.14<NA><NA><NA><NA><NA><NA><NA>
1<NA>작성기준 :<NA>2022.08 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>52,8683,8042,4745,9254,1494,4584,868<NA>2,4302,3892,2803,6145,2394,0737,165
4<NA>전월말인구수<NA><NA><NA>103,4324,9153,85610,8449,7068,45210,426<NA>4,2134,4303,0487,63611,2838,71115,912
5<NA>전월말거주불명자수<NA><NA><NA>8718311294446537<NA>434162776523125
6<NA>전월말재외국민등록자수<NA><NA><NA>10076131265<NA>36391488
7<NA>증 가 요 인전 입계<NA>3,258208921001,87010991<NA>8562897388272119
8<NA><NA><NA>남자<NA>1,68210251619555551<NA>453450394613954
9<NA><NA><NA>여자<NA>1,57610641399155440<NA>402839344213365
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>2000100<NA>0001000
26<NA><NA>국외<NA><NA>0000000<NA>0000000
27<NA><NA>기타<NA><NA>0000000<NA>0000000
28<NA>세대수증감<NA><NA><NA>8549322-28706-18-27<NA>1614240-376-21
29<NA>인구수증감<NA><NA><NA>1,7059412-891,780-84-81<NA>-51119-27-9183-99
30<NA>거주불명자수증감<NA><NA><NA>4205-10-1<NA>00-10000
31<NA>금월말세대수<NA><NA><NA>53,7223,8972,4965,8974,8554,4404,841<NA>2,4462,4032,3043,6145,2364,1497,144
32<NA>금월말인구수<NA><NA><NA>105,1375,0093,86810,75511,4868,36810,345<NA>4,2084,4413,0677,60911,2748,89415,813
33<NA>금월말거주불명자수<NA><NA><NA>8758511299436536<NA>434161776523125
34<NA>금월말재외국민등록자수<NA><NA><NA>10176141266<NA>36391487

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