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

Description2024-01-26
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 10:14:53.362730
Analysis finished2024-02-10 10:14:59.551671
Duration6.19 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
2024-02-10T10:14:59.779020image/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%
2024-02-10T10:15:00.743111image/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
2024-02-10T10:15:01.442449image/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%
2024-02-10T10:15:02.305298image/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
2024-02-10T10:15:02.723480image/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 row2023.10 현재
3rd row계
4th row남자
5th row여자
ValueCountFrequency (%)
계 2
14.3%
남자 2
14.3%
여자 2
14.3%
시도내 2
14.3%
시도간 2
14.3%
광주광역시 1
7.1%
동구 1
7.1%
2023.10 1
7.1%
현재 1
7.1%
2024-02-10T10:15:03.528559image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
시 5
 
12.2%
자 4
 
9.8%
도 4
 
9.8%
3
 
7.3%
계 2
 
4.9%
여 2
 
4.9%
내 2
 
4.9%
간 2
 
4.9%
광 2
 
4.9%
남 2
 
4.9%
Other values (11) 13
31.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 31
75.6%
Decimal Number 6
 
14.6%
Space Separator 3
 
7.3%
Other Punctuation 1
 
2.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 5
16.1%
자 4
12.9%
도 4
12.9%
계 2
 
6.5%
여 2
 
6.5%
내 2
 
6.5%
간 2
 
6.5%
광 2
 
6.5%
남 2
 
6.5%
현 1
 
3.2%
Other values (5) 5
16.1%
Decimal Number
ValueCountFrequency (%)
2 2
33.3%
0 2
33.3%
3 1
16.7%
1 1
16.7%
Space Separator
ValueCountFrequency (%)
3
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 31
75.6%
Common 10
 
24.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 5
16.1%
자 4
12.9%
도 4
12.9%
계 2
 
6.5%
여 2
 
6.5%
내 2
 
6.5%
간 2
 
6.5%
광 2
 
6.5%
남 2
 
6.5%
현 1
 
3.2%
Other values (5) 5
16.1%
Common
ValueCountFrequency (%)
3
30.0%
2 2
20.0%
0 2
20.0%
3 1
 
10.0%
1 1
 
10.0%
. 1
 
10.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 31
75.6%
ASCII 10
 
24.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
시 5
16.1%
자 4
12.9%
도 4
12.9%
계 2
 
6.5%
여 2
 
6.5%
내 2
 
6.5%
간 2
 
6.5%
광 2
 
6.5%
남 2
 
6.5%
현 1
 
3.2%
Other values (5) 5
16.1%
ASCII
ValueCountFrequency (%)
3
30.0%
2 2
20.0%
0 2
20.0%
3 1
 
10.0%
1 1
 
10.0%
. 1
 
10.0%

Unnamed: 4
Text

MISSING 

Distinct2
Distinct (%)50.0%
Missing31
Missing (%)88.6%
Memory size412.0 B
2024-02-10T10:15:03.891942image/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%
2024-02-10T10:15:04.831514image/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 

Distinct29
Distinct (%)87.9%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T10:15:05.236330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length3
Mean length3.1212121
Min length1

Characters and Unicode

Total characters103
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

Unique27 ?
Unique (%)81.8%

Sample

1st row합 계
2nd row54,985
3rd row106,675
4th row697
5th row114
ValueCountFrequency (%)
0 4
 
11.8%
316 2
 
5.9%
1,310 1
 
2.9%
634 1
 
2.9%
106,957 1
 
2.9%
55,107 1
 
2.9%
63 1
 
2.9%
282 1
 
2.9%
122 1
 
2.9%
66 1
 
2.9%
Other values (20) 20
58.8%
2024-02-10T10:15:06.641748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 15
14.6%
6 15
14.6%
0 11
10.7%
3 9
8.7%
5 8
7.8%
7 8
7.8%
4 7
6.8%
8 7
6.8%
, 6
 
5.8%
9 6
 
5.8%
Other values (5) 11
10.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 92
89.3%
Other Punctuation 6
 
5.8%
Space Separator 2
 
1.9%
Other Letter 2
 
1.9%
Dash Punctuation 1
 
1.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 15
16.3%
6 15
16.3%
0 11
12.0%
3 9
9.8%
5 8
8.7%
7 8
8.7%
4 7
7.6%
8 7
7.6%
9 6
 
6.5%
2 6
 
6.5%
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 101
98.1%
Hangul 2
 
1.9%

Most frequent character per script

Common
ValueCountFrequency (%)
1 15
14.9%
6 15
14.9%
0 11
10.9%
3 9
8.9%
5 8
7.9%
7 8
7.9%
4 7
6.9%
8 7
6.9%
, 6
 
5.9%
9 6
 
5.9%
Other values (3) 9
8.9%
Hangul
ValueCountFrequency (%)
합 1
50.0%
계 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 101
98.1%
Hangul 2
 
1.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 15
14.9%
6 15
14.9%
0 11
10.9%
3 9
8.9%
5 8
7.9%
7 8
7.9%
4 7
6.9%
8 7
6.9%
, 6
 
5.9%
9 6
 
5.9%
Other values (3) 9
8.9%
Hangul
ValueCountFrequency (%)
합 1
50.0%
계 1
50.0%

Unnamed: 6
Text

MISSING 

Distinct21
Distinct (%)63.6%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T10:15:07.098072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
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

Unique15 ?
Unique (%)45.5%

Sample

1st row충장동
2nd row4,251
3rd row5,365
4th row36
5th row6
ValueCountFrequency (%)
0 7
21.2%
6 3
 
9.1%
36 2
 
6.1%
105 2
 
6.1%
56 2
 
6.1%
2 2
 
6.1%
4 1
 
3.0%
44 1
 
3.0%
5,361 1
 
3.0%
4,253 1
 
3.0%
Other values (11) 11
33.3%
2024-02-10T10:15:08.096991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6 11
15.9%
5 10
14.5%
0 9
13.0%
1 8
11.6%
4 8
11.6%
3 7
10.1%
2 5
7.2%
, 4
 
5.8%
- 2
 
2.9%
9 1
 
1.4%
Other values (4) 4
 
5.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 60
87.0%
Other Punctuation 4
 
5.8%
Other Letter 3
 
4.3%
Dash Punctuation 2
 
2.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
6 11
18.3%
5 10
16.7%
0 9
15.0%
1 8
13.3%
4 8
13.3%
3 7
11.7%
2 5
8.3%
9 1
 
1.7%
7 1
 
1.7%
Other Letter
ValueCountFrequency (%)
충 1
33.3%
장 1
33.3%
동 1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
6 11
16.7%
5 10
15.2%
0 9
13.6%
1 8
12.1%
4 8
12.1%
3 7
10.6%
2 5
7.6%
, 4
 
6.1%
- 2
 
3.0%
9 1
 
1.5%
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 (%)
6 11
16.7%
5 10
15.2%
0 9
13.6%
1 8
12.1%
4 8
12.1%
3 7
10.6%
2 5
7.6%
, 4
 
6.1%
- 2
 
3.0%
9 1
 
1.5%
Hangul
ValueCountFrequency (%)
충 1
33.3%
장 1
33.3%
동 1
33.3%

Unnamed: 7
Text

MISSING 

Distinct25
Distinct (%)75.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T10:15:08.478949image/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

Unique23 ?
Unique (%)69.7%

Sample

1st row동명동
2nd row2,449
3rd row3,716
4th row118
5th row7
ValueCountFrequency (%)
0 8
24.2%
7 2
 
6.1%
36 1
 
3.0%
44 1
 
3.0%
3,683 1
 
3.0%
2,423 1
 
3.0%
1 1
 
3.0%
33 1
 
3.0%
26 1
 
3.0%
4 1
 
3.0%
Other values (15) 15
45.5%
2024-02-10T10:15:09.534479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 12
16.9%
0 9
12.7%
2 8
11.3%
3 8
11.3%
4 7
9.9%
8 5
7.0%
6 5
7.0%
, 4
 
5.6%
7 3
 
4.2%
9 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 12
19.4%
0 9
14.5%
2 8
12.9%
3 8
12.9%
4 7
11.3%
8 5
8.1%
6 5
8.1%
7 3
 
4.8%
9 3
 
4.8%
5 2
 
3.2%
Other Letter
ValueCountFrequency (%)
동 2
66.7%
명 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 12
17.6%
0 9
13.2%
2 8
11.8%
3 8
11.8%
4 7
10.3%
8 5
7.4%
6 5
7.4%
, 4
 
5.9%
7 3
 
4.4%
9 3
 
4.4%
Other values (2) 4
 
5.9%
Hangul
ValueCountFrequency (%)
동 2
66.7%
명 1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 12
17.6%
0 9
13.2%
2 8
11.8%
3 8
11.8%
4 7
10.3%
8 5
7.4%
6 5
7.4%
, 4
 
5.9%
7 3
 
4.4%
9 3
 
4.4%
Other values (2) 4
 
5.9%
Hangul
ValueCountFrequency (%)
동 2
66.7%
명 1
33.3%

Unnamed: 8
Text

MISSING 

Distinct19
Distinct (%)57.6%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T10:15:10.023328image/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

Unique13 ?
Unique (%)39.4%

Sample

1st row계림1동
2nd row5,749
3rd row10,445
4th row76
5th row12
ValueCountFrequency (%)
0 8
24.2%
11 3
 
9.1%
85 3
 
9.1%
76 2
 
6.1%
12 2
 
6.1%
73 2
 
6.1%
29 1
 
3.0%
30 1
 
3.0%
5,720 1
 
3.0%
24 1
 
3.0%
Other values (9) 9
27.3%
2024-02-10T10:15:10.948747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 15
19.2%
0 14
17.9%
5 7
9.0%
7 7
9.0%
4 7
9.0%
2 6
 
7.7%
, 4
 
5.1%
9 4
 
5.1%
8 3
 
3.8%
6 3
 
3.8%
Other values (5) 8
10.3%

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 14
20.3%
5 7
10.1%
7 7
10.1%
4 7
10.1%
2 6
 
8.7%
9 4
 
5.8%
8 3
 
4.3%
6 3
 
4.3%
3 3
 
4.3%
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 75
96.2%
Hangul 3
 
3.8%

Most frequent character per script

Common
ValueCountFrequency (%)
1 15
20.0%
0 14
18.7%
5 7
9.3%
7 7
9.3%
4 7
9.3%
2 6
 
8.0%
, 4
 
5.3%
9 4
 
5.3%
8 3
 
4.0%
6 3
 
4.0%
Other values (2) 5
 
6.7%
Hangul
ValueCountFrequency (%)
계 1
33.3%
림 1
33.3%
동 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 14
18.7%
5 7
9.3%
7 7
9.3%
4 7
9.3%
2 6
 
8.0%
, 4
 
5.3%
9 4
 
5.3%
8 3
 
4.0%
6 3
 
4.0%
Other values (2) 5
 
6.7%
Hangul
ValueCountFrequency (%)
계 1
33.3%
림 1
33.3%
동 1
33.3%

Unnamed: 9
Text

MISSING 

Distinct22
Distinct (%)66.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T10:15:11.415005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length2
Mean length2.3030303
Min length1

Characters and Unicode

Total characters76
Distinct characters14
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique19 ?
Unique (%)57.6%

Sample

1st row계림2동
2nd row5,658
3rd row13,353
4th row27
5th row11
ValueCountFrequency (%)
0 8
24.2%
11 4
 
12.1%
27 2
 
6.1%
76 1
 
3.0%
130 1
 
3.0%
5,675 1
 
3.0%
17 1
 
3.0%
13 1
 
3.0%
36 1
 
3.0%
73 1
 
3.0%
Other values (12) 12
36.4%
2024-02-10T10:15:12.386998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 16
21.1%
3 12
15.8%
0 10
13.2%
7 9
11.8%
5 6
 
7.9%
2 5
 
6.6%
6 5
 
6.6%
, 4
 
5.3%
4 4
 
5.3%
8 1
 
1.3%
Other values (4) 4
 
5.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 69
90.8%
Other Punctuation 4
 
5.3%
Other Letter 3
 
3.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 16
23.2%
3 12
17.4%
0 10
14.5%
7 9
13.0%
5 6
 
8.7%
2 5
 
7.2%
6 5
 
7.2%
4 4
 
5.8%
8 1
 
1.4%
9 1
 
1.4%
Other Letter
ValueCountFrequency (%)
계 1
33.3%
림 1
33.3%
동 1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
1 16
21.9%
3 12
16.4%
0 10
13.7%
7 9
12.3%
5 6
 
8.2%
2 5
 
6.8%
6 5
 
6.8%
, 4
 
5.5%
4 4
 
5.5%
8 1
 
1.4%
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 (%)
1 16
21.9%
3 12
16.4%
0 10
13.7%
7 9
12.3%
5 6
 
8.2%
2 5
 
6.8%
6 5
 
6.8%
, 4
 
5.5%
4 4
 
5.5%
8 1
 
1.4%
Hangul
ValueCountFrequency (%)
계 1
33.3%
림 1
33.3%
동 1
33.3%

Unnamed: 10
Text

MISSING 

Distinct28
Distinct (%)82.4%
Missing1
Missing (%)2.9%
Memory size412.0 B
2024-02-10T10:15:12.822530image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.2647059
Min length1

Characters and Unicode

Total characters77
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

Unique26 ?
Unique (%)76.5%

Sample

1st row출력일자 :
2nd row산수1동
3rd row4,347
4th row8,064
5th row62
ValueCountFrequency (%)
0 6
 
17.1%
6 2
 
5.7%
9 2
 
5.7%
1
 
2.9%
출력일자 1
 
2.9%
54 1
 
2.9%
8,028 1
 
2.9%
4,342 1
 
2.9%
36 1
 
2.9%
5 1
 
2.9%
Other values (18) 18
51.4%
2024-02-10T10:15:13.636725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4 11
14.3%
0 8
10.4%
6 8
10.4%
3 7
9.1%
2 6
7.8%
5 6
7.8%
8 5
 
6.5%
9 5
 
6.5%
1 4
 
5.2%
, 4
 
5.2%
Other values (11) 13
16.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 61
79.2%
Other Letter 7
 
9.1%
Other Punctuation 5
 
6.5%
Dash Punctuation 3
 
3.9%
Space Separator 1
 
1.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 11
18.0%
0 8
13.1%
6 8
13.1%
3 7
11.5%
2 6
9.8%
5 6
9.8%
8 5
8.2%
9 5
8.2%
1 4
 
6.6%
7 1
 
1.6%
Other Letter
ValueCountFrequency (%)
력 1
14.3%
자 1
14.3%
일 1
14.3%
출 1
14.3%
동 1
14.3%
수 1
14.3%
산 1
14.3%
Other Punctuation
ValueCountFrequency (%)
, 4
80.0%
: 1
 
20.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 70
90.9%
Hangul 7
 
9.1%

Most frequent character per script

Common
ValueCountFrequency (%)
4 11
15.7%
0 8
11.4%
6 8
11.4%
3 7
10.0%
2 6
8.6%
5 6
8.6%
8 5
7.1%
9 5
7.1%
1 4
 
5.7%
, 4
 
5.7%
Other values (4) 6
8.6%
Hangul
ValueCountFrequency (%)
력 1
14.3%
자 1
14.3%
일 1
14.3%
출 1
14.3%
동 1
14.3%
수 1
14.3%
산 1
14.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 70
90.9%
Hangul 7
 
9.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4 11
15.7%
0 8
11.4%
6 8
11.4%
3 7
10.0%
2 6
8.6%
5 6
8.6%
8 5
7.1%
9 5
7.1%
1 4
 
5.7%
, 4
 
5.7%
Other values (4) 6
8.6%
Hangul
ValueCountFrequency (%)
력 1
14.3%
자 1
14.3%
일 1
14.3%
출 1
14.3%
동 1
14.3%
수 1
14.3%
산 1
14.3%

Unnamed: 11
Text

MISSING 

Distinct24
Distinct (%)72.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T10:15:13.953696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
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

Unique21 ?
Unique (%)63.6%

Sample

1st row산수2동
2nd row4,690
3rd row9,873
4th row25
5th row7
ValueCountFrequency (%)
0 6
18.2%
7 3
 
9.1%
49 3
 
9.1%
1 2
 
6.1%
28 1
 
3.0%
52 1
 
3.0%
9,871 1
 
3.0%
4,678 1
 
3.0%
2 1
 
3.0%
12 1
 
3.0%
Other values (13) 13
39.4%
2024-02-10T10:15:14.771469image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 10
14.1%
9 9
12.7%
2 9
12.7%
4 7
9.9%
8 7
9.9%
7 6
8.5%
1 6
8.5%
, 4
 
5.6%
5 3
 
4.2%
- 3
 
4.2%
Other values (5) 7
9.9%

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 (%)
0 10
16.4%
9 9
14.8%
2 9
14.8%
4 7
11.5%
8 7
11.5%
7 6
9.8%
1 6
9.8%
5 3
 
4.9%
6 2
 
3.3%
3 2
 
3.3%
Other Letter
ValueCountFrequency (%)
산 1
33.3%
수 1
33.3%
동 1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
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%
9 9
13.2%
2 9
13.2%
4 7
10.3%
8 7
10.3%
7 6
8.8%
1 6
8.8%
, 4
 
5.9%
5 3
 
4.4%
- 3
 
4.4%
Other values (2) 4
 
5.9%
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%
9 9
13.2%
2 9
13.2%
4 7
10.3%
8 7
10.3%
7 6
8.8%
1 6
8.8%
, 4
 
5.9%
5 3
 
4.4%
- 3
 
4.4%
Other values (2) 4
 
5.9%
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
Minimum2024-01-03 00:00:00
Maximum2024-01-03 00:00:00
2024-02-10T10:15:15.129468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-10T10:15:15.602980image/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
2024-02-10T10:15:15.849276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
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

Unique17 ?
Unique (%)51.5%

Sample

1st row지산1동
2nd row2,462
3rd row4,144
4th row42
5th row3
ValueCountFrequency (%)
0 7
21.2%
3 3
 
9.1%
25 2
 
6.1%
45 2
 
6.1%
15 2
 
6.1%
14 2
 
6.1%
6 2
 
6.1%
4,144 1
 
3.0%
42 1
 
3.0%
26 1
 
3.0%
Other values (10) 10
30.3%
2024-02-10T10:15:16.652662image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4 12
17.4%
1 11
15.9%
0 9
13.0%
2 9
13.0%
5 8
11.6%
6 5
7.2%
3 4
 
5.8%
, 4
 
5.8%
- 2
 
2.9%
9 1
 
1.4%
Other values (4) 4
 
5.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 60
87.0%
Other Punctuation 4
 
5.8%
Other Letter 3
 
4.3%
Dash Punctuation 2
 
2.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 12
20.0%
1 11
18.3%
0 9
15.0%
2 9
15.0%
5 8
13.3%
6 5
8.3%
3 4
 
6.7%
9 1
 
1.7%
8 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 (%)
- 2
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%
1 11
16.7%
0 9
13.6%
2 9
13.6%
5 8
12.1%
6 5
7.6%
3 4
 
6.1%
, 4
 
6.1%
- 2
 
3.0%
9 1
 
1.5%
Hangul
ValueCountFrequency (%)
지 1
33.3%
산 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%
1 11
16.7%
0 9
13.6%
2 9
13.6%
5 8
12.1%
6 5
7.6%
3 4
 
6.1%
, 4
 
6.1%
- 2
 
3.0%
9 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
2024-02-10T10:15:16.959901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length2.0606061
Min length1

Characters and Unicode

Total characters68
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 row지산2동
2nd row2,373
3rd row4,319
4th row9
5th row7
ValueCountFrequency (%)
0 8
24.2%
7 3
 
9.1%
24 3
 
9.1%
16 2
 
6.1%
23 1
 
3.0%
9 1
 
3.0%
42 1
 
3.0%
13 1
 
3.0%
4,296 1
 
3.0%
2,366 1
 
3.0%
Other values (11) 11
33.3%
2024-02-10T10:15:17.856676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 9
13.2%
2 9
13.2%
4 8
11.8%
1 8
11.8%
3 7
10.3%
6 6
8.8%
7 4
5.9%
9 4
5.9%
, 4
5.9%
8 2
 
2.9%
Other values (5) 7
10.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 59
86.8%
Other Punctuation 4
 
5.9%
Other Letter 3
 
4.4%
Dash Punctuation 2
 
2.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 9
15.3%
2 9
15.3%
4 8
13.6%
1 8
13.6%
3 7
11.9%
6 6
10.2%
7 4
6.8%
9 4
6.8%
8 2
 
3.4%
5 2
 
3.4%
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 65
95.6%
Hangul 3
 
4.4%

Most frequent character per script

Common
ValueCountFrequency (%)
0 9
13.8%
2 9
13.8%
4 8
12.3%
1 8
12.3%
3 7
10.8%
6 6
9.2%
7 4
6.2%
9 4
6.2%
, 4
6.2%
8 2
 
3.1%
Other values (2) 4
6.2%
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 9
13.8%
2 9
13.8%
4 8
12.3%
1 8
12.3%
3 7
10.8%
6 6
9.2%
7 4
6.2%
9 4
6.2%
, 4
6.2%
8 2
 
3.1%
Other values (2) 4
6.2%
Hangul
ValueCountFrequency (%)
지 1
33.3%
산 1
33.3%
동 1
33.3%

Unnamed: 15
Text

MISSING 

Distinct23
Distinct (%)69.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T10:15:18.163815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
Mean length1.969697
Min length1

Characters and Unicode

Total characters65
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 row서남동
2nd row2,310
3rd row3,023
4th row52
5th row5
ValueCountFrequency (%)
0 8
24.2%
5 2
 
6.1%
52 2
 
6.1%
6 2
 
6.1%
16 1
 
3.0%
3,023 1
 
3.0%
27 1
 
3.0%
2,316 1
 
3.0%
2,310 1
 
3.0%
3 1
 
3.0%
Other values (13) 13
39.4%
2024-02-10T10:15:18.972643image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 12
18.5%
0 11
16.9%
3 9
13.8%
1 8
12.3%
6 6
9.2%
5 6
9.2%
, 4
 
6.2%
8 2
 
3.1%
9 2
 
3.1%
4 1
 
1.5%
Other values (4) 4
 
6.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 58
89.2%
Other Punctuation 4
 
6.2%
Other Letter 3
 
4.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 12
20.7%
0 11
19.0%
3 9
15.5%
1 8
13.8%
6 6
10.3%
5 6
10.3%
8 2
 
3.4%
9 2
 
3.4%
4 1
 
1.7%
7 1
 
1.7%
Other Letter
ValueCountFrequency (%)
서 1
33.3%
남 1
33.3%
동 1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
2 12
19.4%
0 11
17.7%
3 9
14.5%
1 8
12.9%
6 6
9.7%
5 6
9.7%
, 4
 
6.5%
8 2
 
3.2%
9 2
 
3.2%
4 1
 
1.6%
Hangul
ValueCountFrequency (%)
서 1
33.3%
남 1
33.3%
동 1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 12
19.4%
0 11
17.7%
3 9
14.5%
1 8
12.9%
6 6
9.7%
5 6
9.7%
, 4
 
6.5%
8 2
 
3.2%
9 2
 
3.2%
4 1
 
1.6%
Hangul
ValueCountFrequency (%)
서 1
33.3%
남 1
33.3%
동 1
33.3%

Unnamed: 16
Text

MISSING 

Distinct26
Distinct (%)78.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T10:15:19.310646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length2
Mean length2.2121212
Min length1

Characters and Unicode

Total characters73
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 row학동
2nd row3,524
3rd row7,356
4th row77
5th row10
ValueCountFrequency (%)
0 6
 
18.2%
10 2
 
6.1%
32 2
 
6.1%
39 1
 
3.0%
7,338 1
 
3.0%
3,495 1
 
3.0%
27 1
 
3.0%
18 1
 
3.0%
29 1
 
3.0%
25 1
 
3.0%
Other values (16) 16
48.5%
2024-02-10T10:15:20.104590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 10
13.7%
0 9
12.3%
3 9
12.3%
7 8
11.0%
1 7
9.6%
5 5
6.8%
, 4
 
5.5%
4 4
 
5.5%
6 4
 
5.5%
8 4
 
5.5%
Other values (4) 9
12.3%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 10
15.6%
0 9
14.1%
3 9
14.1%
7 8
12.5%
1 7
10.9%
5 5
7.8%
4 4
 
6.2%
6 4
 
6.2%
8 4
 
6.2%
9 4
 
6.2%
Other Letter
ValueCountFrequency (%)
학 1
50.0%
동 1
50.0%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 71
97.3%
Hangul 2
 
2.7%

Most frequent character per script

Common
ValueCountFrequency (%)
2 10
14.1%
0 9
12.7%
3 9
12.7%
7 8
11.3%
1 7
9.9%
5 5
7.0%
, 4
 
5.6%
4 4
 
5.6%
6 4
 
5.6%
8 4
 
5.6%
Other values (2) 7
9.9%
Hangul
ValueCountFrequency (%)
학 1
50.0%
동 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 71
97.3%
Hangul 2
 
2.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 10
14.1%
0 9
12.7%
3 9
12.7%
7 8
11.3%
1 7
9.9%
5 5
7.0%
, 4
 
5.6%
4 4
 
5.6%
6 4
 
5.6%
8 4
 
5.6%
Other values (2) 7
9.9%
Hangul
ValueCountFrequency (%)
학 1
50.0%
동 1
50.0%

Unnamed: 17
Text

MISSING 

Distinct28
Distinct (%)84.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T10:15:20.441632image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length2
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

Unique26 ?
Unique (%)78.8%

Sample

1st row학운동
2nd row5,185
3rd row11,080
4th row45
5th row24
ValueCountFrequency (%)
0 5
 
15.2%
24 3
 
9.1%
22 2
 
6.1%
51 1
 
3.0%
11,056 1
 
3.0%
5,160 1
 
3.0%
25 1
 
3.0%
8 1
 
3.0%
31 1
 
3.0%
26 1
 
3.0%
Other values (16) 16
48.5%
2024-02-10T10:15:21.170434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 12
15.8%
0 10
13.2%
5 10
13.2%
1 9
11.8%
4 7
9.2%
6 6
7.9%
3 5
6.6%
, 4
 
5.3%
8 4
 
5.3%
- 3
 
3.9%
Other values (5) 6
7.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 66
86.8%
Other Punctuation 4
 
5.3%
Dash Punctuation 3
 
3.9%
Other Letter 3
 
3.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 12
18.2%
0 10
15.2%
5 10
15.2%
1 9
13.6%
4 7
10.6%
6 6
9.1%
3 5
7.6%
8 4
 
6.1%
9 2
 
3.0%
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 (%)
- 3
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
2 12
16.4%
0 10
13.7%
5 10
13.7%
1 9
12.3%
4 7
9.6%
6 6
8.2%
3 5
6.8%
, 4
 
5.5%
8 4
 
5.5%
- 3
 
4.1%
Other values (2) 3
 
4.1%
Hangul
ValueCountFrequency (%)
학 1
33.3%
운 1
33.3%
동 1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 12
16.4%
0 10
13.7%
5 10
13.7%
1 9
12.3%
4 7
9.6%
6 6
8.2%
3 5
6.8%
, 4
 
5.5%
8 4
 
5.5%
- 3
 
4.1%
Other values (2) 3
 
4.1%
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
2024-02-10T10:15:21.593945image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
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

Unique20 ?
Unique (%)60.6%

Sample

1st row지원1동
2nd row4,276
3rd row9,111
4th row22
5th row9
ValueCountFrequency (%)
0 7
21.2%
9 3
 
9.1%
21 2
 
6.1%
7 2
 
6.1%
41 1
 
3.0%
22 1
 
3.0%
83 1
 
3.0%
4,267 1
 
3.0%
1 1
 
3.0%
28 1
 
3.0%
Other values (13) 13
39.4%
2024-02-10T10:15:22.458047image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 11
15.5%
0 10
14.1%
2 9
12.7%
3 6
8.5%
9 5
7.0%
4 5
7.0%
7 4
 
5.6%
5 4
 
5.6%
, 4
 
5.6%
6 4
 
5.6%
Other values (5) 9
12.7%

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 (%)
1 11
18.0%
0 10
16.4%
2 9
14.8%
3 6
9.8%
9 5
8.2%
4 5
8.2%
7 4
 
6.6%
5 4
 
6.6%
6 4
 
6.6%
8 3
 
4.9%
Other Letter
ValueCountFrequency (%)
지 1
33.3%
원 1
33.3%
동 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 (%)
1 11
16.2%
0 10
14.7%
2 9
13.2%
3 6
8.8%
9 5
7.4%
4 5
7.4%
7 4
 
5.9%
5 4
 
5.9%
, 4
 
5.9%
6 4
 
5.9%
Other values (2) 6
8.8%
Hangul
ValueCountFrequency (%)
지 1
33.3%
원 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 (%)
1 11
16.2%
0 10
14.7%
2 9
13.2%
3 6
8.8%
9 5
7.4%
4 5
7.4%
7 4
 
5.9%
5 4
 
5.9%
, 4
 
5.9%
6 4
 
5.9%
Other values (2) 6
8.8%
Hangul
ValueCountFrequency (%)
지 1
33.3%
원 1
33.3%
동 1
33.3%

Unnamed: 19
Text

MISSING 

Distinct27
Distinct (%)81.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T10:15:22.809010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.5151515
Min length1

Characters and Unicode

Total characters83
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 row지원2동
2nd row7,711
3rd row16,826
4th row106
5th row7
ValueCountFrequency (%)
0 6
 
18.2%
7 2
 
6.1%
10 2
 
6.1%
74 1
 
3.0%
17,297 1
 
3.0%
7,956 1
 
3.0%
471 1
 
3.0%
245 1
 
3.0%
13 1
 
3.0%
41 1
 
3.0%
Other values (16) 16
48.5%
2024-02-10T10:15:23.518245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 13
15.7%
0 12
14.5%
7 10
12.0%
6 9
10.8%
4 7
8.4%
9 7
8.4%
5 6
7.2%
2 5
 
6.0%
, 4
 
4.8%
3 4
 
4.8%
Other values (5) 6
7.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 75
90.4%
Other Punctuation 4
 
4.8%
Other Letter 3
 
3.6%
Dash Punctuation 1
 
1.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 13
17.3%
0 12
16.0%
7 10
13.3%
6 9
12.0%
4 7
9.3%
9 7
9.3%
5 6
8.0%
2 5
 
6.7%
3 4
 
5.3%
8 2
 
2.7%
Other Letter
ValueCountFrequency (%)
지 1
33.3%
원 1
33.3%
동 1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 80
96.4%
Hangul 3
 
3.6%

Most frequent character per script

Common
ValueCountFrequency (%)
1 13
16.2%
0 12
15.0%
7 10
12.5%
6 9
11.2%
4 7
8.8%
9 7
8.8%
5 6
7.5%
2 5
 
6.2%
, 4
 
5.0%
3 4
 
5.0%
Other values (2) 3
 
3.8%
Hangul
ValueCountFrequency (%)
지 1
33.3%
원 1
33.3%
동 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 80
96.4%
Hangul 3
 
3.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 13
16.2%
0 12
15.0%
7 10
12.5%
6 9
11.2%
4 7
8.8%
9 7
8.8%
5 6
7.5%
2 5
 
6.2%
, 4
 
5.0%
3 4
 
5.0%
Other values (2) 3
 
3.8%
Hangul
ValueCountFrequency (%)
지 1
33.3%
원 1
33.3%
동 1
33.3%

Correlations

2024-02-10T10:15:23.819751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
인구이동보고서(1호)Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 6Unnamed: 7Unnamed: 8Unnamed: 9Unnamed: 10Unnamed: 11Unnamed: 13Unnamed: 14Unnamed: 15Unnamed: 16Unnamed: 17Unnamed: 18Unnamed: 19
인구이동보고서(1호)1.0000.0001.000NaN1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
Unnamed: 20.0001.000NaNNaN0.9401.0001.0001.0001.0001.0000.9251.0001.0001.0001.0001.0001.0001.000
Unnamed: 31.000NaN1.000NaN1.0001.0001.0000.5831.0001.0000.7900.7900.5831.0001.0001.0001.0001.000
Unnamed: 4NaNNaNNaN1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
Unnamed: 51.0000.9401.0001.0001.0000.9850.9900.9890.9870.9920.9890.9870.9920.9880.9910.9930.9890.992
Unnamed: 61.0001.0001.0001.0000.9851.0000.9960.9480.9680.9960.9850.9640.9660.9710.9881.0000.9860.996
Unnamed: 71.0001.0001.0001.0000.9900.9961.0000.9970.9981.0000.9920.9930.9950.9940.9951.0000.9971.000
Unnamed: 81.0001.0000.5831.0000.9890.9480.9971.0000.9881.0000.9850.9680.9720.9920.9931.0000.9941.000
Unnamed: 91.0001.0001.0001.0000.9870.9680.9980.9881.0001.0000.9850.9940.9870.9970.9931.0000.9911.000
Unnamed: 101.0001.0001.0001.0000.9920.9961.0001.0001.0001.0000.9931.0000.9941.0001.0001.0001.0001.000
Unnamed: 111.0000.9250.7901.0000.9890.9850.9920.9850.9850.9931.0000.9830.9770.9750.9880.9930.9950.993
Unnamed: 131.0001.0000.7901.0000.9870.9640.9930.9680.9941.0000.9831.0000.9860.9860.9951.0000.9901.000
Unnamed: 141.0001.0000.5831.0000.9920.9660.9950.9720.9870.9940.9770.9861.0000.9620.9840.9930.9870.994
Unnamed: 151.0001.0001.0001.0000.9880.9710.9940.9920.9971.0000.9750.9860.9621.0000.9931.0000.9891.000
Unnamed: 161.0001.0001.0001.0000.9910.9880.9950.9930.9931.0000.9880.9950.9840.9931.0001.0000.9941.000
Unnamed: 171.0001.0001.0001.0000.9931.0001.0001.0001.0001.0000.9931.0000.9931.0001.0001.0001.0001.000
Unnamed: 181.0001.0001.0001.0000.9890.9860.9970.9940.9911.0000.9950.9900.9870.9890.9941.0001.0001.000
Unnamed: 191.0001.0001.0001.0000.9920.9961.0001.0001.0001.0000.9931.0000.9941.0001.0001.0001.0001.000

Missing values

2024-02-10T10:14:57.068235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-02-10T10:14:58.015186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2024-02-10T10:14:58.745035image/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>2023.10 현재<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
2<NA>시, 군, 구(읍면동)<NA><NA><NA>합 계충장동동명동계림1동계림2동산수1동산수2동<NA>지산1동지산2동서남동학동학운동지원1동지원2동
3<NA>전월말세대수<NA><NA><NA>54,9854,2512,4495,7495,6584,3474,690<NA>2,4622,3732,3103,5245,1854,2767,711
4<NA>전월말인구수<NA><NA><NA>106,6755,3653,71610,44513,3538,0649,873<NA>4,1444,3193,0237,35611,0809,11116,826
5<NA>전월말거주불명자수<NA><NA><NA>6973611876276225<NA>42952774522106
6<NA>전월말재외국민등록자수<NA><NA><NA>11467121167<NA>375102497
7<NA>증 가 요 인전 입계<NA>1,690105511461439498<NA>454261769683650
8<NA><NA><NA>남자<NA>838492873724849<NA>252428484633315
9<NA><NA><NA>여자<NA>852562373714649<NA>201833285050335
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>66000090<NA>0002522010
26<NA><NA>국외<NA><NA>0000000<NA>0000000
27<NA><NA>기타<NA><NA>0000000<NA>0000000
28<NA>세대수증감<NA><NA><NA>1222-26-2917-5-12<NA>-6-76-29-25-9245
29<NA>인구수증감<NA><NA><NA>282-4-33-2411-36-2<NA>-14-236-18-24-28471
30<NA>거주불명자수증감<NA><NA><NA>-63-1100-9-1<NA>340-27-22-1-10
31<NA>금월말세대수<NA><NA><NA>55,1074,2532,4235,7205,6754,3424,678<NA>2,4562,3662,3163,4955,1604,2677,956
32<NA>금월말인구수<NA><NA><NA>106,9575,3613,68310,42113,3648,0289,871<NA>4,1304,2963,0297,33811,0569,08317,297
33<NA>금월말거주불명자수<NA><NA><NA>6343511976275324<NA>45135250232196
34<NA>금월말재외국민등록자수<NA><NA><NA>11367121167<NA>365102497

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