Overview

Dataset statistics

Number of variables28
Number of observations35
Missing cells207
Missing cells (%)21.1%
Duplicate rows2
Duplicate rows (%)5.7%
Total size in memory7.8 KiB
Average record size in memory228.8 B

Variable types

Unsupported1
Text25
DateTime1
Categorical1

Dataset

Description2022-12-16
Author주민등록인구통계
URLhttps://bigdata.gwangju.go.kr/usr/dataSet/getDataDetailView.rd?dataSetUncd=DS000201924

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: 20 has 2 (5.7%) missing valuesMissing
Unnamed: 21 has 2 (5.7%) missing valuesMissing
Unnamed: 22 has 2 (5.7%) missing valuesMissing
Unnamed: 23 has 2 (5.7%) missing valuesMissing
Unnamed: 24 has 2 (5.7%) missing valuesMissing
Unnamed: 25 has 2 (5.7%) missing valuesMissing
Unnamed: 27 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 06:45:52.246277
Analysis finished2024-02-10 06:45:53.673589
Duration1.43 second
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
2024-02-10T06:45:53.978540image/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%
2024-02-10T06:45:54.971162image/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
2024-02-10T06:45:55.390363image/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%
2024-02-10T06:45:56.792638image/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
2024-02-10T06:45:57.252801image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length3
Mean length3.5
Min length1

Characters and Unicode

Total characters42
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 광산구
2nd row2022.11 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%
광산구 1
7.1%
2022.11 1
7.1%
현재 1
7.1%
2024-02-10T06:45:58.180090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
시 5
11.9%
자 4
 
9.5%
도 4
 
9.5%
광 3
 
7.1%
3
 
7.1%
2 3
 
7.1%
계 2
 
4.8%
여 2
 
4.8%
내 2
 
4.8%
간 2
 
4.8%
Other values (10) 12
28.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 32
76.2%
Decimal Number 6
 
14.3%
Space Separator 3
 
7.1%
Other Punctuation 1
 
2.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 5
15.6%
자 4
12.5%
도 4
12.5%
광 3
9.4%
계 2
 
6.2%
여 2
 
6.2%
내 2
 
6.2%
간 2
 
6.2%
남 2
 
6.2%
현 1
 
3.1%
Other values (5) 5
15.6%
Decimal Number
ValueCountFrequency (%)
2 3
50.0%
1 2
33.3%
0 1
 
16.7%
Space Separator
ValueCountFrequency (%)
3
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 32
76.2%
Common 10
 
23.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 5
15.6%
자 4
12.5%
도 4
12.5%
광 3
9.4%
계 2
 
6.2%
여 2
 
6.2%
내 2
 
6.2%
간 2
 
6.2%
남 2
 
6.2%
현 1
 
3.1%
Other values (5) 5
15.6%
Common
ValueCountFrequency (%)
3
30.0%
2 3
30.0%
1 2
20.0%
0 1
 
10.0%
. 1
 
10.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 32
76.2%
ASCII 10
 
23.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
시 5
15.6%
자 4
12.5%
도 4
12.5%
광 3
9.4%
계 2
 
6.2%
여 2
 
6.2%
내 2
 
6.2%
간 2
 
6.2%
남 2
 
6.2%
현 1
 
3.1%
Other values (5) 5
15.6%
ASCII
ValueCountFrequency (%)
3
30.0%
2 3
30.0%
1 2
20.0%
0 1
 
10.0%
. 1
 
10.0%

Unnamed: 4
Text

MISSING 

Distinct2
Distinct (%)50.0%
Missing31
Missing (%)88.6%
Memory size412.0 B
2024-02-10T06:45:58.643766image/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%
2024-02-10T06:45:59.517690image/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
2024-02-10T06:45:59.955226image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length3.7878788
Min length1

Characters and Unicode

Total characters125
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

Unique26 ?
Unique (%)78.8%

Sample

1st row합 계
2nd row170,834
3rd row401,334
4th row676
5th row140
ValueCountFrequency (%)
0 5
 
14.7%
1,176 2
 
5.9%
1,789 1
 
2.9%
1,859 1
 
2.9%
672 1
 
2.9%
400,895 1
 
2.9%
170,774 1
 
2.9%
4 1
 
2.9%
439 1
 
2.9%
60 1
 
2.9%
Other values (19) 19
55.9%
2024-02-10T06:46:00.886561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 23
18.4%
4 17
13.6%
0 15
12.0%
, 15
12.0%
7 12
9.6%
6 9
 
7.2%
3 9
 
7.2%
9 6
 
4.8%
8 5
 
4.0%
5 5
 
4.0%
Other values (5) 9
 
7.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 103
82.4%
Other Punctuation 15
 
12.0%
Dash Punctuation 3
 
2.4%
Space Separator 2
 
1.6%
Other Letter 2
 
1.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 23
22.3%
4 17
16.5%
0 15
14.6%
7 12
11.7%
6 9
 
8.7%
3 9
 
8.7%
9 6
 
5.8%
8 5
 
4.9%
5 5
 
4.9%
2 2
 
1.9%
Other Letter
ValueCountFrequency (%)
합 1
50.0%
계 1
50.0%
Other Punctuation
ValueCountFrequency (%)
, 15
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 123
98.4%
Hangul 2
 
1.6%

Most frequent character per script

Common
ValueCountFrequency (%)
1 23
18.7%
4 17
13.8%
0 15
12.2%
, 15
12.2%
7 12
9.8%
6 9
 
7.3%
3 9
 
7.3%
9 6
 
4.9%
8 5
 
4.1%
5 5
 
4.1%
Other values (3) 7
 
5.7%
Hangul
ValueCountFrequency (%)
합 1
50.0%
계 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 123
98.4%
Hangul 2
 
1.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 23
18.7%
4 17
13.8%
0 15
12.2%
, 15
12.2%
7 12
9.8%
6 9
 
7.3%
3 9
 
7.3%
9 6
 
4.9%
8 5
 
4.1%
5 5
 
4.1%
Other values (3) 7
 
5.7%
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
2024-02-10T06:46:01.310321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
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

Unique21 ?
Unique (%)63.6%

Sample

1st row송정1동
2nd row4,806
3rd row10,603
4th row26
5th row1
ValueCountFrequency (%)
0 6
18.2%
1 5
 
15.2%
25 2
 
6.1%
4,806 1
 
3.0%
26 1
 
3.0%
47 1
 
3.0%
4,796 1
 
3.0%
14 1
 
3.0%
10 1
 
3.0%
7 1
 
3.0%
Other values (13) 13
39.4%
2024-02-10T06:46:02.164901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 12
16.4%
1 12
16.4%
4 8
11.0%
2 6
8.2%
6 6
8.2%
5 4
 
5.5%
8 4
 
5.5%
3 4
 
5.5%
9 4
 
5.5%
, 4
 
5.5%
Other values (5) 9
12.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 63
86.3%
Other Punctuation 4
 
5.5%
Dash Punctuation 3
 
4.1%
Other Letter 3
 
4.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 12
19.0%
1 12
19.0%
4 8
12.7%
2 6
9.5%
6 6
9.5%
5 4
 
6.3%
8 4
 
6.3%
3 4
 
6.3%
9 4
 
6.3%
7 3
 
4.8%
Other Letter
ValueCountFrequency (%)
송 1
33.3%
정 1
33.3%
동 1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
0 12
17.1%
1 12
17.1%
4 8
11.4%
2 6
8.6%
6 6
8.6%
5 4
 
5.7%
8 4
 
5.7%
3 4
 
5.7%
9 4
 
5.7%
, 4
 
5.7%
Other values (2) 6
8.6%
Hangul
ValueCountFrequency (%)
송 1
33.3%
정 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 12
17.1%
1 12
17.1%
4 8
11.4%
2 6
8.6%
6 6
8.6%
5 4
 
5.7%
8 4
 
5.7%
3 4
 
5.7%
9 4
 
5.7%
, 4
 
5.7%
Other values (2) 6
8.6%
Hangul
ValueCountFrequency (%)
송 1
33.3%
정 1
33.3%
동 1
33.3%

Unnamed: 7
Text

MISSING 

Distinct24
Distinct (%)72.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T06:46:02.675103image/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 row송정2동
2nd row3,442
3rd row6,377
4th row59
5th row7
ValueCountFrequency (%)
0 7
21.2%
7 2
 
6.1%
59 2
 
6.1%
3 2
 
6.1%
42 1
 
3.0%
6,377 1
 
3.0%
88 1
 
3.0%
6,360 1
 
3.0%
3,436 1
 
3.0%
1 1
 
3.0%
Other values (14) 14
42.4%
2024-02-10T06:46:03.656549image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 11
15.5%
0 9
12.7%
6 7
9.9%
4 6
8.5%
2 6
8.5%
7 5
7.0%
5 5
7.0%
9 5
7.0%
, 4
 
5.6%
8 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 (%)
3 11
18.0%
0 9
14.8%
6 7
11.5%
4 6
9.8%
2 6
9.8%
7 5
8.2%
5 5
8.2%
9 5
8.2%
8 4
 
6.6%
1 3
 
4.9%
Other Letter
ValueCountFrequency (%)
송 1
33.3%
정 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 (%)
3 11
16.2%
0 9
13.2%
6 7
10.3%
4 6
8.8%
2 6
8.8%
7 5
7.4%
5 5
7.4%
9 5
7.4%
, 4
 
5.9%
8 4
 
5.9%
Other values (2) 6
8.8%
Hangul
ValueCountFrequency (%)
송 1
33.3%
정 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 (%)
3 11
16.2%
0 9
13.2%
6 7
10.3%
4 6
8.8%
2 6
8.8%
7 5
7.4%
5 5
7.4%
9 5
7.4%
, 4
 
5.9%
8 4
 
5.9%
Other values (2) 6
8.8%
Hangul
ValueCountFrequency (%)
송 1
33.3%
정 1
33.3%
동 1
33.3%

Unnamed: 8
Text

MISSING 

Distinct24
Distinct (%)72.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T06:46:04.069571image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
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

Unique20 ?
Unique (%)60.6%

Sample

1st row도산동
2nd row6,642
3rd row14,915
4th row21
5th row3
ValueCountFrequency (%)
0 7
21.2%
3 2
 
6.1%
63 2
 
6.1%
38 2
 
6.1%
21 2
 
6.1%
9 1
 
3.0%
82 1
 
3.0%
6,624 1
 
3.0%
18 1
 
3.0%
7 1
 
3.0%
Other values (13) 13
39.4%
2024-02-10T06:46:04.974207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 9
12.3%
1 9
12.3%
6 9
12.3%
3 8
11.0%
4 7
9.6%
8 7
9.6%
2 6
8.2%
7 5
6.8%
, 4
5.5%
9 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 9
14.1%
1 9
14.1%
6 9
14.1%
3 8
12.5%
4 7
10.9%
8 7
10.9%
2 6
9.4%
7 5
7.8%
9 2
 
3.1%
5 2
 
3.1%
Other Letter
ValueCountFrequency (%)
도 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 70
95.9%
Hangul 3
 
4.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 9
12.9%
1 9
12.9%
6 9
12.9%
3 8
11.4%
4 7
10.0%
8 7
10.0%
2 6
8.6%
7 5
7.1%
, 4
5.7%
9 2
 
2.9%
Other values (2) 4
5.7%
Hangul
ValueCountFrequency (%)
도 1
33.3%
산 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 9
12.9%
1 9
12.9%
6 9
12.9%
3 8
11.4%
4 7
10.0%
8 7
10.0%
2 6
8.6%
7 5
7.1%
, 4
5.7%
9 2
 
2.9%
Other values (2) 4
5.7%
Hangul
ValueCountFrequency (%)
도 1
33.3%
산 1
33.3%
동 1
33.3%

Unnamed: 9
Text

MISSING 

Distinct25
Distinct (%)75.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T06:46:05.367296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
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

Unique22 ?
Unique (%)66.7%

Sample

1st row신흥동
2nd row2,033
3rd row4,458
4th row16
5th row3
ValueCountFrequency (%)
0 7
21.2%
19 2
 
6.1%
2 2
 
6.1%
1 2
 
6.1%
3 2
 
6.1%
26 1
 
3.0%
31 1
 
3.0%
4,446 1
 
3.0%
2,031 1
 
3.0%
12 1
 
3.0%
Other values (13) 13
39.4%
2024-02-10T06:46:06.700467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 12
17.6%
2 10
14.7%
0 9
13.2%
3 7
10.3%
4 7
10.3%
5 4
 
5.9%
, 4
 
5.9%
6 4
 
5.9%
- 3
 
4.4%
9 2
 
2.9%
Other values (5) 6
8.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 58
85.3%
Other Punctuation 4
 
5.9%
Dash Punctuation 3
 
4.4%
Other Letter 3
 
4.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 12
20.7%
2 10
17.2%
0 9
15.5%
3 7
12.1%
4 7
12.1%
5 4
 
6.9%
6 4
 
6.9%
9 2
 
3.4%
7 2
 
3.4%
8 1
 
1.7%
Other Letter
ValueCountFrequency (%)
신 1
33.3%
흥 1
33.3%
동 1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
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%
2 10
15.4%
0 9
13.8%
3 7
10.8%
4 7
10.8%
5 4
 
6.2%
, 4
 
6.2%
6 4
 
6.2%
- 3
 
4.6%
9 2
 
3.1%
Other values (2) 3
 
4.6%
Hangul
ValueCountFrequency (%)
신 1
33.3%
흥 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%
2 10
15.4%
0 9
13.8%
3 7
10.8%
4 7
10.8%
5 4
 
6.2%
, 4
 
6.2%
6 4
 
6.2%
- 3
 
4.6%
9 2
 
3.1%
Other values (2) 3
 
4.6%
Hangul
ValueCountFrequency (%)
신 1
33.3%
흥 1
33.3%
동 1
33.3%

Unnamed: 10
Text

MISSING 

Distinct27
Distinct (%)79.4%
Missing1
Missing (%)2.9%
Memory size412.0 B
2024-02-10T06:46:07.273712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length3
Mean length2.6176471
Min length1

Characters and Unicode

Total characters89
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

Unique25 ?
Unique (%)73.5%

Sample

1st row출력일자 :
2nd row어룡동
3rd row14,223
4th row33,197
5th row29
ValueCountFrequency (%)
0 7
 
20.0%
6 2
 
5.7%
1
 
2.9%
출력일자 1
 
2.9%
287 1
 
2.9%
33,233 1
 
2.9%
14,257 1
 
2.9%
2 1
 
2.9%
36 1
 
2.9%
34 1
 
2.9%
Other values (18) 18
51.4%
2024-02-10T06:46:08.569961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 14
15.7%
2 13
14.6%
3 12
13.5%
0 8
9.0%
7 7
7.9%
4 7
7.9%
5 4
 
4.5%
6 4
 
4.5%
9 4
 
4.5%
, 4
 
4.5%
Other values (11) 12
13.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 75
84.3%
Other Letter 7
 
7.9%
Other Punctuation 5
 
5.6%
Dash Punctuation 1
 
1.1%
Space Separator 1
 
1.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 14
18.7%
2 13
17.3%
3 12
16.0%
0 8
10.7%
7 7
9.3%
4 7
9.3%
5 4
 
5.3%
6 4
 
5.3%
9 4
 
5.3%
8 2
 
2.7%
Other Letter
ValueCountFrequency (%)
동 1
14.3%
룡 1
14.3%
어 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 (%)
- 1
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 82
92.1%
Hangul 7
 
7.9%

Most frequent character per script

Common
ValueCountFrequency (%)
1 14
17.1%
2 13
15.9%
3 12
14.6%
0 8
9.8%
7 7
8.5%
4 7
8.5%
5 4
 
4.9%
6 4
 
4.9%
9 4
 
4.9%
, 4
 
4.9%
Other values (4) 5
 
6.1%
Hangul
ValueCountFrequency (%)
동 1
14.3%
룡 1
14.3%
어 1
14.3%
출 1
14.3%
력 1
14.3%
일 1
14.3%
자 1
14.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 82
92.1%
Hangul 7
 
7.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 14
17.1%
2 13
15.9%
3 12
14.6%
0 8
9.8%
7 7
8.5%
4 7
8.5%
5 4
 
4.9%
6 4
 
4.9%
9 4
 
4.9%
, 4
 
4.9%
Other values (4) 5
 
6.1%
Hangul
ValueCountFrequency (%)
동 1
14.3%
룡 1
14.3%
어 1
14.3%
출 1
14.3%
력 1
14.3%
일 1
14.3%
자 1
14.3%

Unnamed: 11
Text

MISSING 

Distinct25
Distinct (%)75.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T06:46:09.105070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length3
Mean length2.3636364
Min length1

Characters and Unicode

Total characters78
Distinct characters15
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique22 ?
Unique (%)66.7%

Sample

1st row우산동
2nd row15,072
3rd row29,629
4th row81
5th row8
ValueCountFrequency (%)
0 7
21.2%
7 2
 
6.1%
8 2
 
6.1%
27 1
 
3.0%
241 1
 
3.0%
29,636 1
 
3.0%
15,079 1
 
3.0%
2 1
 
3.0%
14 1
 
3.0%
69 1
 
3.0%
Other values (15) 15
45.5%
2024-02-10T06:46:10.497088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 11
14.1%
7 11
14.1%
1 11
14.1%
2 10
12.8%
9 8
10.3%
6 6
7.7%
8 4
 
5.1%
5 4
 
5.1%
, 4
 
5.1%
3 3
 
3.8%
Other values (5) 6
7.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 70
89.7%
Other Punctuation 4
 
5.1%
Other Letter 3
 
3.8%
Dash Punctuation 1
 
1.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 11
15.7%
7 11
15.7%
1 11
15.7%
2 10
14.3%
9 8
11.4%
6 6
8.6%
8 4
 
5.7%
5 4
 
5.7%
3 3
 
4.3%
4 2
 
2.9%
Other Letter
ValueCountFrequency (%)
우 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 75
96.2%
Hangul 3
 
3.8%

Most frequent character per script

Common
ValueCountFrequency (%)
0 11
14.7%
7 11
14.7%
1 11
14.7%
2 10
13.3%
9 8
10.7%
6 6
8.0%
8 4
 
5.3%
5 4
 
5.3%
, 4
 
5.3%
3 3
 
4.0%
Other values (2) 3
 
4.0%
Hangul
ValueCountFrequency (%)
우 1
33.3%
산 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 (%)
0 11
14.7%
7 11
14.7%
1 11
14.7%
2 10
13.3%
9 8
10.7%
6 6
8.0%
8 4
 
5.3%
5 4
 
5.3%
, 4
 
5.3%
3 3
 
4.0%
Other values (2) 3
 
4.0%
Hangul
ValueCountFrequency (%)
우 1
33.3%
산 1
33.3%
동 1
33.3%

Unnamed: 12
Date

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing34
Missing (%)97.1%
Memory size412.0 B
Minimum2022-12-01 00:00:00
Maximum2022-12-01 00:00:00
2024-02-10T06:46:10.983955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-10T06:46:11.338942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Unnamed: 13
Text

MISSING 

Distinct25
Distinct (%)75.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T06:46:11.637513image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
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

Unique21 ?
Unique (%)63.6%

Sample

1st row월곡1동
2nd row4,852
3rd row10,428
4th row25
5th row7
ValueCountFrequency (%)
0 6
18.2%
7 2
 
6.1%
37 2
 
6.1%
48 2
 
6.1%
70 2
 
6.1%
68 1
 
3.0%
10,380 1
 
3.0%
4,825 1
 
3.0%
3 1
 
3.0%
27 1
 
3.0%
Other values (14) 14
42.4%
2024-02-10T06:46:12.500138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

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

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 12
18.8%
8 11
17.2%
2 10
15.6%
7 7
10.9%
3 7
10.9%
4 5
7.8%
1 4
 
6.2%
5 4
 
6.2%
6 3
 
4.7%
9 1
 
1.6%
Other Letter
ValueCountFrequency (%)
월 1
33.3%
곡 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 12
17.1%
8 11
15.7%
2 10
14.3%
7 7
10.0%
3 7
10.0%
4 5
7.1%
1 4
 
5.7%
, 4
 
5.7%
5 4
 
5.7%
6 3
 
4.3%
Other values (2) 3
 
4.3%
Hangul
ValueCountFrequency (%)
월 1
33.3%
곡 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 12
17.1%
8 11
15.7%
2 10
14.3%
7 7
10.0%
3 7
10.0%
4 5
7.1%
1 4
 
5.7%
, 4
 
5.7%
5 4
 
5.7%
6 3
 
4.3%
Other values (2) 3
 
4.3%
Hangul
ValueCountFrequency (%)
월 1
33.3%
곡 1
33.3%
동 1
33.3%

Unnamed: 14
Text

MISSING 

Distinct26
Distinct (%)78.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T06:46:12.837933image/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

Unique24 ?
Unique (%)72.7%

Sample

1st row월곡2동
2nd row6,465
3rd row15,045
4th row30
5th row7
ValueCountFrequency (%)
0 6
 
18.2%
7 3
 
9.1%
149 1
 
3.0%
14,989 1
 
3.0%
6,442 1
 
3.0%
2 1
 
3.0%
56 1
 
3.0%
23 1
 
3.0%
35 1
 
3.0%
36 1
 
3.0%
Other values (16) 16
48.5%
2024-02-10T06:46:13.663200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 9
12.2%
2 9
12.2%
5 8
10.8%
4 7
9.5%
3 6
8.1%
6 6
8.1%
8 6
8.1%
9 5
6.8%
7 4
 
5.4%
, 4
 
5.4%
Other values (5) 10
13.5%

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 (%)
0 9
14.1%
2 9
14.1%
5 8
12.5%
4 7
10.9%
3 6
9.4%
6 6
9.4%
8 6
9.4%
9 5
7.8%
7 4
6.2%
1 4
6.2%
Other Letter
ValueCountFrequency (%)
월 1
33.3%
곡 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 (%)
0 9
12.7%
2 9
12.7%
5 8
11.3%
4 7
9.9%
3 6
8.5%
6 6
8.5%
8 6
8.5%
9 5
7.0%
7 4
5.6%
, 4
5.6%
Other values (2) 7
9.9%
Hangul
ValueCountFrequency (%)
월 1
33.3%
곡 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 9
12.7%
2 9
12.7%
5 8
11.3%
4 7
9.9%
3 6
8.5%
6 6
8.5%
8 6
8.5%
9 5
7.0%
7 4
5.6%
, 4
5.6%
Other values (2) 7
9.9%
Hangul
ValueCountFrequency (%)
월 1
33.3%
곡 1
33.3%
동 1
33.3%

Unnamed: 15
Text

MISSING 

Distinct24
Distinct (%)72.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T06:46:13.977500image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length2
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

Unique20 ?
Unique (%)60.6%

Sample

1st row비아동
2nd row3,539
3rd row7,554
4th row27
5th row5
ValueCountFrequency (%)
0 7
21.2%
36 2
 
6.1%
31 2
 
6.1%
5 2
 
6.1%
3 1
 
3.0%
45 1
 
3.0%
7,545 1
 
3.0%
3,532 1
 
3.0%
1 1
 
3.0%
9 1
 
3.0%
Other values (14) 14
42.4%
2024-02-10T06:46:14.792921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 11
16.2%
5 10
14.7%
0 8
11.8%
2 6
8.8%
1 5
7.4%
7 5
7.4%
4 5
7.4%
6 4
 
5.9%
, 4
 
5.9%
- 3
 
4.4%
Other values (5) 7
10.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 58
85.3%
Other Punctuation 4
 
5.9%
Dash Punctuation 3
 
4.4%
Other Letter 3
 
4.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 11
19.0%
5 10
17.2%
0 8
13.8%
2 6
10.3%
1 5
8.6%
7 5
8.6%
4 5
8.6%
6 4
 
6.9%
8 2
 
3.4%
9 2
 
3.4%
Other Letter
ValueCountFrequency (%)
비 1
33.3%
아 1
33.3%
동 1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
3 11
16.9%
5 10
15.4%
0 8
12.3%
2 6
9.2%
1 5
7.7%
7 5
7.7%
4 5
7.7%
6 4
 
6.2%
, 4
 
6.2%
- 3
 
4.6%
Other values (2) 4
 
6.2%
Hangul
ValueCountFrequency (%)
비 1
33.3%
아 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 (%)
3 11
16.9%
5 10
15.4%
0 8
12.3%
2 6
9.2%
1 5
7.7%
7 5
7.7%
4 5
7.7%
6 4
 
6.2%
, 4
 
6.2%
- 3
 
4.6%
Other values (2) 4
 
6.2%
Hangul
ValueCountFrequency (%)
비 1
33.3%
아 1
33.3%
동 1
33.3%

Unnamed: 16
Text

MISSING 

Distinct27
Distinct (%)81.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T06:46:15.145621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length4
Mean length2.4545455
Min length1

Characters and Unicode

Total characters81
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 row첨단1동
2nd row10,555
3rd row27,060
4th row21
5th row14
ValueCountFrequency (%)
0 6
 
18.2%
21 2
 
6.1%
108 1
 
3.0%
206 1
 
3.0%
19 1
 
3.0%
27,080 1
 
3.0%
10,576 1
 
3.0%
2 1
 
3.0%
20 1
 
3.0%
11 1
 
3.0%
Other values (17) 17
51.5%
2024-02-10T06:46:15.825918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 17
21.0%
1 14
17.3%
2 10
12.3%
6 8
9.9%
5 7
8.6%
8 6
 
7.4%
, 4
 
4.9%
7 4
 
4.9%
3 3
 
3.7%
4 2
 
2.5%
Other values (5) 6
 
7.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 73
90.1%
Other Punctuation 4
 
4.9%
Other Letter 3
 
3.7%
Dash Punctuation 1
 
1.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 17
23.3%
1 14
19.2%
2 10
13.7%
6 8
11.0%
5 7
9.6%
8 6
 
8.2%
7 4
 
5.5%
3 3
 
4.1%
4 2
 
2.7%
9 2
 
2.7%
Other Letter
ValueCountFrequency (%)
첨 1
33.3%
단 1
33.3%
동 1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 78
96.3%
Hangul 3
 
3.7%

Most frequent character per script

Common
ValueCountFrequency (%)
0 17
21.8%
1 14
17.9%
2 10
12.8%
6 8
10.3%
5 7
9.0%
8 6
 
7.7%
, 4
 
5.1%
7 4
 
5.1%
3 3
 
3.8%
4 2
 
2.6%
Other values (2) 3
 
3.8%
Hangul
ValueCountFrequency (%)
첨 1
33.3%
단 1
33.3%
동 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 78
96.3%
Hangul 3
 
3.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 17
21.8%
1 14
17.9%
2 10
12.8%
6 8
10.3%
5 7
9.0%
8 6
 
7.7%
, 4
 
5.1%
7 4
 
5.1%
3 3
 
3.8%
4 2
 
2.6%
Other values (2) 3
 
3.8%
Hangul
ValueCountFrequency (%)
첨 1
33.3%
단 1
33.3%
동 1
33.3%

Unnamed: 17
Text

MISSING 

Distinct25
Distinct (%)75.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T06:46:16.233077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length4
Mean length2.7272727
Min length1

Characters and Unicode

Total characters90
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 row첨단2동
2nd row18,679
3rd row42,713
4th row68
5th row23
ValueCountFrequency (%)
0 7
21.2%
15 2
 
6.1%
23 2
 
6.1%
224 1
 
3.0%
68 1
 
3.0%
42,713 1
 
3.0%
42,600 1
 
3.0%
18,665 1
 
3.0%
2 1
 
3.0%
113 1
 
3.0%
Other values (15) 15
45.5%
2024-02-10T06:46:17.020245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 16
17.8%
2 13
14.4%
0 12
13.3%
6 10
11.1%
4 8
8.9%
3 6
 
6.7%
5 5
 
5.6%
9 4
 
4.4%
8 4
 
4.4%
, 4
 
4.4%
Other values (5) 8
8.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 80
88.9%
Other Punctuation 4
 
4.4%
Dash Punctuation 3
 
3.3%
Other Letter 3
 
3.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 16
20.0%
2 13
16.2%
0 12
15.0%
6 10
12.5%
4 8
10.0%
3 6
 
7.5%
5 5
 
6.2%
9 4
 
5.0%
8 4
 
5.0%
7 2
 
2.5%
Other Letter
ValueCountFrequency (%)
첨 1
33.3%
단 1
33.3%
동 1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 87
96.7%
Hangul 3
 
3.3%

Most frequent character per script

Common
ValueCountFrequency (%)
1 16
18.4%
2 13
14.9%
0 12
13.8%
6 10
11.5%
4 8
9.2%
3 6
 
6.9%
5 5
 
5.7%
9 4
 
4.6%
8 4
 
4.6%
, 4
 
4.6%
Other values (2) 5
 
5.7%
Hangul
ValueCountFrequency (%)
첨 1
33.3%
단 1
33.3%
동 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 87
96.7%
Hangul 3
 
3.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 16
18.4%
2 13
14.9%
0 12
13.8%
6 10
11.5%
4 8
9.2%
3 6
 
6.9%
5 5
 
5.7%
9 4
 
4.6%
8 4
 
4.6%
, 4
 
4.6%
Other values (2) 5
 
5.7%
Hangul
ValueCountFrequency (%)
첨 1
33.3%
단 1
33.3%
동 1
33.3%

Unnamed: 18
Text

MISSING 

Distinct24
Distinct (%)72.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T06:46:17.344629image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.1515152
Min length1

Characters and Unicode

Total characters71
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 row신가동
2nd row7,417
3rd row19,448
4th row33
5th row5
ValueCountFrequency (%)
0 7
21.2%
36 3
 
9.1%
5 2
 
6.1%
48 1
 
3.0%
33 1
 
3.0%
75 1
 
3.0%
7,421 1
 
3.0%
3 1
 
3.0%
17 1
 
3.0%
4 1
 
3.0%
Other values (14) 14
42.4%
2024-02-10T06:46:18.084032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 9
12.7%
1 9
12.7%
7 9
12.7%
0 8
11.3%
4 8
11.3%
6 7
9.9%
5 6
8.5%
8 4
5.6%
, 4
5.6%
2 2
 
2.8%
Other values (4) 5
7.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 64
90.1%
Other Punctuation 4
 
5.6%
Other Letter 3
 
4.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 9
14.1%
1 9
14.1%
7 9
14.1%
0 8
12.5%
4 8
12.5%
6 7
10.9%
5 6
9.4%
8 4
6.2%
2 2
 
3.1%
9 2
 
3.1%
Other Letter
ValueCountFrequency (%)
신 1
33.3%
가 1
33.3%
동 1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
3 9
13.2%
1 9
13.2%
7 9
13.2%
0 8
11.8%
4 8
11.8%
6 7
10.3%
5 6
8.8%
8 4
5.9%
, 4
5.9%
2 2
 
2.9%
Hangul
ValueCountFrequency (%)
신 1
33.3%
가 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 (%)
3 9
13.2%
1 9
13.2%
7 9
13.2%
0 8
11.8%
4 8
11.8%
6 7
10.3%
5 6
8.8%
8 4
5.9%
, 4
5.9%
2 2
 
2.9%
Hangul
ValueCountFrequency (%)
신 1
33.3%
가 1
33.3%
동 1
33.3%

Unnamed: 19
Text

MISSING 

Distinct24
Distinct (%)72.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T06:46:18.420313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length3
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

Unique20 ?
Unique (%)60.6%

Sample

1st row운남동
2nd row12,268
3rd row30,225
4th row20
5th row10
ValueCountFrequency (%)
0 7
21.2%
12,268 2
 
6.1%
10 2
 
6.1%
1 2
 
6.1%
20 1
 
3.0%
213 1
 
3.0%
30,177 1
 
3.0%
48 1
 
3.0%
18 1
 
3.0%
77 1
 
3.0%
Other values (14) 14
42.4%
2024-02-10T06:46:19.164107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 16
20.3%
0 13
16.5%
2 11
13.9%
8 9
11.4%
7 6
 
7.6%
3 5
 
6.3%
, 4
 
5.1%
6 4
 
5.1%
5 3
 
3.8%
4 3
 
3.8%
Other values (5) 5
 
6.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 71
89.9%
Other Punctuation 4
 
5.1%
Other Letter 3
 
3.8%
Dash Punctuation 1
 
1.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 16
22.5%
0 13
18.3%
2 11
15.5%
8 9
12.7%
7 6
 
8.5%
3 5
 
7.0%
6 4
 
5.6%
5 3
 
4.2%
4 3
 
4.2%
9 1
 
1.4%
Other Letter
ValueCountFrequency (%)
운 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 76
96.2%
Hangul 3
 
3.8%

Most frequent character per script

Common
ValueCountFrequency (%)
1 16
21.1%
0 13
17.1%
2 11
14.5%
8 9
11.8%
7 6
 
7.9%
3 5
 
6.6%
, 4
 
5.3%
6 4
 
5.3%
5 3
 
3.9%
4 3
 
3.9%
Other values (2) 2
 
2.6%
Hangul
ValueCountFrequency (%)
운 1
33.3%
남 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 16
21.1%
0 13
17.1%
2 11
14.5%
8 9
11.8%
7 6
 
7.9%
3 5
 
6.6%
, 4
 
5.3%
6 4
 
5.3%
5 3
 
3.9%
4 3
 
3.9%
Other values (2) 2
 
2.6%
Hangul
ValueCountFrequency (%)
운 1
33.3%
남 1
33.3%
동 1
33.3%

Unnamed: 20
Text

MISSING 

Distinct27
Distinct (%)81.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T06:46:19.486753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length4
Mean length2.7575758
Min length1

Characters and Unicode

Total characters91
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 row수완동
2nd row28,199
3rd row75,958
4th row89
5th row15
ValueCountFrequency (%)
0 6
 
18.2%
15 2
 
6.1%
1 2
 
6.1%
286 1
 
3.0%
75,853 1
 
3.0%
28,177 1
 
3.0%
105 1
 
3.0%
22 1
 
3.0%
17 1
 
3.0%
224 1
 
3.0%
Other values (16) 16
48.5%
2024-02-10T06:46:20.396060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 14
15.4%
2 14
15.4%
0 12
13.2%
5 10
11.0%
8 10
11.0%
7 8
8.8%
3 4
 
4.4%
, 4
 
4.4%
9 4
 
4.4%
6 3
 
3.3%
Other values (5) 8
8.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 81
89.0%
Other Punctuation 4
 
4.4%
Dash Punctuation 3
 
3.3%
Other Letter 3
 
3.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 14
17.3%
2 14
17.3%
0 12
14.8%
5 10
12.3%
8 10
12.3%
7 8
9.9%
3 4
 
4.9%
9 4
 
4.9%
6 3
 
3.7%
4 2
 
2.5%
Other Letter
ValueCountFrequency (%)
수 1
33.3%
완 1
33.3%
동 1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 88
96.7%
Hangul 3
 
3.3%

Most frequent character per script

Common
ValueCountFrequency (%)
1 14
15.9%
2 14
15.9%
0 12
13.6%
5 10
11.4%
8 10
11.4%
7 8
9.1%
3 4
 
4.5%
, 4
 
4.5%
9 4
 
4.5%
6 3
 
3.4%
Other values (2) 5
 
5.7%
Hangul
ValueCountFrequency (%)
수 1
33.3%
완 1
33.3%
동 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 88
96.7%
Hangul 3
 
3.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 14
15.9%
2 14
15.9%
0 12
13.6%
5 10
11.4%
8 10
11.4%
7 8
9.1%
3 4
 
4.5%
, 4
 
4.5%
9 4
 
4.5%
6 3
 
3.4%
Other values (2) 5
 
5.7%
Hangul
ValueCountFrequency (%)
수 1
33.3%
완 1
33.3%
동 1
33.3%

Unnamed: 21
Text

MISSING 

Distinct27
Distinct (%)81.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T06:46:20.730577image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length3
Mean length2.3636364
Min length1

Characters and Unicode

Total characters78
Distinct characters14
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique25 ?
Unique (%)75.8%

Sample

1st row하남동
2nd row10,981
3rd row26,550
4th row37
5th row7
ValueCountFrequency (%)
0 6
 
18.2%
7 2
 
6.1%
105 1
 
3.0%
218 1
 
3.0%
26,601 1
 
3.0%
11,044 1
 
3.0%
4 1
 
3.0%
51 1
 
3.0%
63 1
 
3.0%
6 1
 
3.0%
Other values (17) 17
51.5%
2024-02-10T06:46:21.542400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 15
19.2%
0 11
14.1%
7 9
11.5%
6 8
10.3%
2 6
 
7.7%
5 6
 
7.7%
4 6
 
7.7%
, 4
 
5.1%
8 4
 
5.1%
3 4
 
5.1%
Other values (4) 5
 
6.4%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 15
21.1%
0 11
15.5%
7 9
12.7%
6 8
11.3%
2 6
 
8.5%
5 6
 
8.5%
4 6
 
8.5%
8 4
 
5.6%
3 4
 
5.6%
9 2
 
2.8%
Other Letter
ValueCountFrequency (%)
하 1
33.3%
남 1
33.3%
동 1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
1 15
20.0%
0 11
14.7%
7 9
12.0%
6 8
10.7%
2 6
 
8.0%
5 6
 
8.0%
4 6
 
8.0%
, 4
 
5.3%
8 4
 
5.3%
3 4
 
5.3%
Hangul
ValueCountFrequency (%)
하 1
33.3%
남 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 11
14.7%
7 9
12.0%
6 8
10.7%
2 6
 
8.0%
5 6
 
8.0%
4 6
 
8.0%
, 4
 
5.3%
8 4
 
5.3%
3 4
 
5.3%
Hangul
ValueCountFrequency (%)
하 1
33.3%
남 1
33.3%
동 1
33.3%

Unnamed: 22
Text

MISSING 

Distinct18
Distinct (%)54.5%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T06:46:21.868058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length1
Mean length1.7272727
Min length1

Characters and Unicode

Total characters57
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

Unique11 ?
Unique (%)33.3%

Sample

1st row임곡동
2nd row1,244
3rd row2,053
4th row12
5th row2
ValueCountFrequency (%)
0 8
24.2%
4 3
 
9.1%
2 3
 
9.1%
11 2
 
6.1%
8 2
 
6.1%
9 2
 
6.1%
12 2
 
6.1%
임곡동 1
 
3.0%
22 1
 
3.0%
2,053 1
 
3.0%
Other values (8) 8
24.2%
2024-02-10T06:46:22.636863image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 11
19.3%
0 10
17.5%
1 10
17.5%
4 6
10.5%
, 4
 
7.0%
5 3
 
5.3%
8 2
 
3.5%
9 2
 
3.5%
6 2
 
3.5%
3 2
 
3.5%
Other values (4) 5
8.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 50
87.7%
Other Punctuation 4
 
7.0%
Other Letter 3
 
5.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 11
22.0%
0 10
20.0%
1 10
20.0%
4 6
12.0%
5 3
 
6.0%
8 2
 
4.0%
9 2
 
4.0%
6 2
 
4.0%
3 2
 
4.0%
7 2
 
4.0%
Other Letter
ValueCountFrequency (%)
임 1
33.3%
곡 1
33.3%
동 1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 54
94.7%
Hangul 3
 
5.3%

Most frequent character per script

Common
ValueCountFrequency (%)
2 11
20.4%
0 10
18.5%
1 10
18.5%
4 6
11.1%
, 4
 
7.4%
5 3
 
5.6%
8 2
 
3.7%
9 2
 
3.7%
6 2
 
3.7%
3 2
 
3.7%
Hangul
ValueCountFrequency (%)
임 1
33.3%
곡 1
33.3%
동 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 54
94.7%
Hangul 3
 
5.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 11
20.4%
0 10
18.5%
1 10
18.5%
4 6
11.1%
, 4
 
7.4%
5 3
 
5.6%
8 2
 
3.7%
9 2
 
3.7%
6 2
 
3.7%
3 2
 
3.7%
Hangul
ValueCountFrequency (%)
임 1
33.3%
곡 1
33.3%
동 1
33.3%

Unnamed: 23
Text

MISSING 

Distinct17
Distinct (%)51.5%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T06:46:22.958831image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length1
Mean length1.7575758
Min length1

Characters and Unicode

Total characters58
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

Unique11 ?
Unique (%)33.3%

Sample

1st row동곡동
2nd row1,012
3rd row1,787
4th row1
5th row4
ValueCountFrequency (%)
0 8
24.2%
4 4
12.1%
5 3
 
9.1%
1 3
 
9.1%
11 2
 
6.1%
7 2
 
6.1%
동곡동 1
 
3.0%
16 1
 
3.0%
1,787 1
 
3.0%
1,012 1
 
3.0%
Other values (7) 7
21.2%
2024-02-10T06:46:23.666224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 16
27.6%
0 10
17.2%
7 7
12.1%
4 5
 
8.6%
, 4
 
6.9%
2 4
 
6.9%
5 3
 
5.2%
3 2
 
3.4%
8 2
 
3.4%
동 2
 
3.4%
Other values (3) 3
 
5.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 50
86.2%
Other Punctuation 4
 
6.9%
Other Letter 3
 
5.2%
Dash Punctuation 1
 
1.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 16
32.0%
0 10
20.0%
7 7
14.0%
4 5
 
10.0%
2 4
 
8.0%
5 3
 
6.0%
3 2
 
4.0%
8 2
 
4.0%
6 1
 
2.0%
Other Letter
ValueCountFrequency (%)
동 2
66.7%
곡 1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 55
94.8%
Hangul 3
 
5.2%

Most frequent character per script

Common
ValueCountFrequency (%)
1 16
29.1%
0 10
18.2%
7 7
12.7%
4 5
 
9.1%
, 4
 
7.3%
2 4
 
7.3%
5 3
 
5.5%
3 2
 
3.6%
8 2
 
3.6%
- 1
 
1.8%
Hangul
ValueCountFrequency (%)
동 2
66.7%
곡 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 55
94.8%
Hangul 3
 
5.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 16
29.1%
0 10
18.2%
7 7
12.7%
4 5
 
9.1%
, 4
 
7.3%
2 4
 
7.3%
5 3
 
5.5%
3 2
 
3.6%
8 2
 
3.6%
- 1
 
1.8%
Hangul
ValueCountFrequency (%)
동 2
66.7%
곡 1
33.3%

Unnamed: 24
Text

MISSING 

Distinct20
Distinct (%)60.6%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T06:46:24.027019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
Mean length2.030303
Min length1

Characters and Unicode

Total characters67
Distinct characters13
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique15 ?
Unique (%)45.5%

Sample

1st row평동
2nd row2,964
3rd row4,829
4th row13
5th row3
ValueCountFrequency (%)
0 9
27.3%
13 3
 
9.1%
3 2
 
6.1%
21 2
 
6.1%
43 2
 
6.1%
33 1
 
3.0%
2,981 1
 
3.0%
17 1
 
3.0%
6 1
 
3.0%
22 1
 
3.0%
Other values (10) 10
30.3%
2024-02-10T06:46:24.783346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 11
16.4%
3 11
16.4%
0 10
14.9%
2 9
13.4%
4 7
10.4%
, 4
 
6.0%
9 3
 
4.5%
6 3
 
4.5%
8 3
 
4.5%
5 2
 
3.0%
Other values (3) 4
 
6.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 61
91.0%
Other Punctuation 4
 
6.0%
Other Letter 2
 
3.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 11
18.0%
3 11
18.0%
0 10
16.4%
2 9
14.8%
4 7
11.5%
9 3
 
4.9%
6 3
 
4.9%
8 3
 
4.9%
5 2
 
3.3%
7 2
 
3.3%
Other Letter
ValueCountFrequency (%)
평 1
50.0%
동 1
50.0%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
1 11
16.9%
3 11
16.9%
0 10
15.4%
2 9
13.8%
4 7
10.8%
, 4
 
6.2%
9 3
 
4.6%
6 3
 
4.6%
8 3
 
4.6%
5 2
 
3.1%
Hangul
ValueCountFrequency (%)
평 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 (%)
1 11
16.9%
3 11
16.9%
0 10
15.4%
2 9
13.8%
4 7
10.8%
, 4
 
6.2%
9 3
 
4.6%
6 3
 
4.6%
8 3
 
4.6%
5 2
 
3.1%
Hangul
ValueCountFrequency (%)
평 1
50.0%
동 1
50.0%

Unnamed: 25
Text

MISSING 

Distinct18
Distinct (%)54.5%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T06:46:25.078285image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length1
Mean length1.9090909
Min length1

Characters and Unicode

Total characters63
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

Unique13 ?
Unique (%)39.4%

Sample

1st row삼도동
2nd row1,333
3rd row2,182
4th row6
5th row0
ValueCountFrequency (%)
0 11
33.3%
6 3
 
9.1%
15 2
 
6.1%
10 2
 
6.1%
9 2
 
6.1%
14 2
 
6.1%
20 1
 
3.0%
25 1
 
3.0%
2,182 1
 
3.0%
1,333 1
 
3.0%
Other values (7) 7
21.2%
2024-02-10T06:46:25.911394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 14
22.2%
1 12
19.0%
2 7
11.1%
3 6
9.5%
6 4
 
6.3%
5 4
 
6.3%
, 4
 
6.3%
4 3
 
4.8%
9 2
 
3.2%
- 2
 
3.2%
Other values (4) 5
 
7.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 54
85.7%
Other Punctuation 4
 
6.3%
Other Letter 3
 
4.8%
Dash Punctuation 2
 
3.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 14
25.9%
1 12
22.2%
2 7
13.0%
3 6
11.1%
6 4
 
7.4%
5 4
 
7.4%
4 3
 
5.6%
9 2
 
3.7%
8 2
 
3.7%
Other Letter
ValueCountFrequency (%)
삼 1
33.3%
도 1
33.3%
동 1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 60
95.2%
Hangul 3
 
4.8%

Most frequent character per script

Common
ValueCountFrequency (%)
0 14
23.3%
1 12
20.0%
2 7
11.7%
3 6
10.0%
6 4
 
6.7%
5 4
 
6.7%
, 4
 
6.7%
4 3
 
5.0%
9 2
 
3.3%
- 2
 
3.3%
Hangul
ValueCountFrequency (%)
삼 1
33.3%
도 1
33.3%
동 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 60
95.2%
Hangul 3
 
4.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 14
23.3%
1 12
20.0%
2 7
11.7%
3 6
10.0%
6 4
 
6.7%
5 4
 
6.7%
, 4
 
6.7%
4 3
 
5.0%
9 2
 
3.3%
- 2
 
3.3%
Hangul
ValueCountFrequency (%)
삼 1
33.3%
도 1
33.3%
동 1
33.3%

Unnamed: 26
Categorical

Distinct16
Distinct (%)45.7%
Missing0
Missing (%)0.0%
Memory size412.0 B
0
11 
3
5 
4
3 
8
3 
<NA>
2 
Other values (11)
11 

Length

Max length5
Median length1
Mean length1.8571429
Min length1

Unique

Unique11 ?
Unique (%)31.4%

Sample

1st row<NA>
2nd row<NA>
3rd row본량동
4th row1,198
5th row1,945

Common Values

ValueCountFrequency (%)
0 11
31.4%
3 5
14.3%
4 3
 
8.6%
8 3
 
8.6%
<NA> 2
 
5.7%
본량동 1
 
2.9%
1,198 1
 
2.9%
1,945 1
 
2.9%
10 1
 
2.9%
6 1
 
2.9%
Other values (6) 6
17.1%

Length

2024-02-10T06:46:26.295061image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
0 11
31.4%
3 5
14.3%
8 4
 
11.4%
4 3
 
8.6%
na 2
 
5.7%
본량동 1
 
2.9%
1,198 1
 
2.9%
1,945 1
 
2.9%
10 1
 
2.9%
6 1
 
2.9%
Other values (5) 5
14.3%

Unnamed: 27
Text

MISSING 

Distinct26
Distinct (%)78.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T06:46:26.789307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length4
Mean length2.6363636
Min length1

Characters and Unicode

Total characters87
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 row신창동
2nd row13,910
3rd row34,378
4th row59
5th row10
ValueCountFrequency (%)
0 6
 
18.2%
10 3
 
9.1%
364 1
 
3.0%
34,262 1
 
3.0%
13,839 1
 
3.0%
1 1
 
3.0%
116 1
 
3.0%
71 1
 
3.0%
137 1
 
3.0%
133 1
 
3.0%
Other values (16) 16
48.5%
2024-02-10T06:46:27.585232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 18
20.7%
0 13
14.9%
3 11
12.6%
6 7
 
8.0%
2 6
 
6.9%
4 6
 
6.9%
9 5
 
5.7%
, 4
 
4.6%
8 4
 
4.6%
5 4
 
4.6%
Other values (5) 9
10.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 77
88.5%
Other Punctuation 4
 
4.6%
Dash Punctuation 3
 
3.4%
Other Letter 3
 
3.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 18
23.4%
0 13
16.9%
3 11
14.3%
6 7
 
9.1%
2 6
 
7.8%
4 6
 
7.8%
9 5
 
6.5%
8 4
 
5.2%
5 4
 
5.2%
7 3
 
3.9%
Other Letter
ValueCountFrequency (%)
신 1
33.3%
창 1
33.3%
동 1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 84
96.6%
Hangul 3
 
3.4%

Most frequent character per script

Common
ValueCountFrequency (%)
1 18
21.4%
0 13
15.5%
3 11
13.1%
6 7
 
8.3%
2 6
 
7.1%
4 6
 
7.1%
9 5
 
6.0%
, 4
 
4.8%
8 4
 
4.8%
5 4
 
4.8%
Other values (2) 6
 
7.1%
Hangul
ValueCountFrequency (%)
신 1
33.3%
창 1
33.3%
동 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 84
96.6%
Hangul 3
 
3.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 18
21.4%
0 13
15.5%
3 11
13.1%
6 7
 
8.3%
2 6
 
7.1%
4 6
 
7.1%
9 5
 
6.0%
, 4
 
4.8%
8 4
 
4.8%
5 4
 
4.8%
Other values (2) 6
 
7.1%
Hangul
ValueCountFrequency (%)
신 1
33.3%
창 1
33.3%
동 1
33.3%

Sample

Unnamed: 0인구이동보고서(1호)Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 6Unnamed: 7Unnamed: 8Unnamed: 9Unnamed: 10Unnamed: 11Unnamed: 12Unnamed: 13Unnamed: 14Unnamed: 15Unnamed: 16Unnamed: 17Unnamed: 18Unnamed: 19Unnamed: 20Unnamed: 21Unnamed: 22Unnamed: 23Unnamed: 24Unnamed: 25Unnamed: 26Unnamed: 27
0<NA>행정기관 :<NA>광주광역시 광산구<NA><NA><NA><NA><NA><NA>출력일자 :<NA>2022.12.01<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
1<NA>작성기준 :<NA>2022.11 현재<NA><NA><NA><NA><NA><NA><NA><NA><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 계송정1동송정2동도산동신흥동어룡동우산동<NA>월곡1동월곡2동비아동첨단1동첨단2동신가동운남동수완동하남동임곡동동곡동평동삼도동본량동신창동
3<NA>전월말세대수<NA><NA><NA>170,8344,8063,4426,6422,03314,22315,072<NA>4,8526,4653,53910,55518,6797,41712,26828,19910,9811,2441,0122,9641,3331,19813,910
4<NA>전월말인구수<NA><NA><NA>401,33410,6036,37714,9154,45833,19729,629<NA>10,42815,0457,55427,06042,71319,44830,22575,95826,5502,0531,7874,8292,1821,94534,378
5<NA>전월말거주불명자수<NA><NA><NA>676265921162981<NA>253027216833208937121136359
6<NA>전월말재외국민등록자수<NA><NA><NA>140173368<NA>77514235101572430010
7<NA>증 가 요 인전 입계<NA>3,194868812646317235<NA>85927223031316316750025722161042510240
8<NA><NA><NA>남자<NA>1,64046496321175130<NA>3742361041648084252132111161106126
9<NA><NA><NA>여자<NA>1,55440396325142105<NA>485036126149838324812511543154114
Unnamed: 0인구이동보고서(1호)Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 6Unnamed: 7Unnamed: 8Unnamed: 9Unnamed: 10Unnamed: 11Unnamed: 12Unnamed: 13Unnamed: 14Unnamed: 15Unnamed: 16Unnamed: 17Unnamed: 18Unnamed: 19Unnamed: 20Unnamed: 21Unnamed: 22Unnamed: 23Unnamed: 24Unnamed: 25Unnamed: 26Unnamed: 27
25<NA><NA>말소<NA><NA>1000000<NA>000000010000000
26<NA><NA>국외<NA><NA>0000000<NA>000000000000000
27<NA><NA>기타<NA><NA>0000000<NA>000000000000000
28<NA>세대수증감<NA><NA><NA>-60-10-6-18-2347<NA>-27-23-721-1440-22632117-1-8-71
29<NA>인구수증감<NA><NA><NA>-439-14-17-38-12367<NA>-48-56-920-11317-48-105514-1443-14-13-116
30<NA>거주불명자수증감<NA><NA><NA>-4-1-10-1-2-2<NA>3-2-1-2-231-1401000-1
31<NA>금월말세대수<NA><NA><NA>170,7744,7963,4366,6242,03114,25715,079<NA>4,8256,4423,53210,57618,6657,42112,26828,17711,0441,2461,0132,9811,3321,19013,839
32<NA>금월말인구수<NA><NA><NA>400,89510,5896,36014,8774,44633,23329,636<NA>10,38014,9897,54527,08042,60019,46530,17775,85326,6012,0571,7734,8722,1681,93234,262
33<NA>금월말거주불명자수<NA><NA><NA>672255821152779<NA>282826196636218841122136358
34<NA>금월말재외국민등록자수<NA><NA><NA>141173368<NA>77515235101572430010

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: 19Unnamed: 20Unnamed: 21Unnamed: 22Unnamed: 23Unnamed: 24Unnamed: 25Unnamed: 26Unnamed: 27# duplicates
0<NA>국외<NA><NA>0000000<NA>0000000000000002
1<NA>기타<NA><NA>0000000<NA>0000000000000002