Overview

Dataset statistics

Number of variables28
Number of observations35
Missing cells205
Missing cells (%)20.9%
Duplicate rows2
Duplicate rows (%)5.7%
Total size in memory7.8 KiB
Average record size in memory228.8 B

Variable types

Unsupported1
Text24
DateTime1
Categorical2

Dataset

Description2023-11-10
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: 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 07:04:14.414719
Analysis finished2024-02-10 07:04:15.758862
Duration1.34 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
2024-02-10T07:04:16.098931image/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%
2024-02-10T07:04:17.128291image/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
2024-02-10T07:04:17.588463image/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%
2024-02-10T07:04:18.594321image/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
2024-02-10T07:04:19.048405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length3
Mean length3.5
Min length1

Characters and Unicode

Total characters42
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 광산구
2nd row2023.09 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%
2023.09 1
7.1%
현재 1
7.1%
2024-02-10T07:04:19.923592image/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%
계 2
 
4.8%
여 2
 
4.8%
내 2
 
4.8%
간 2
 
4.8%
남 2
 
4.8%
Other values (11) 13
31.0%

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 2
33.3%
0 2
33.3%
3 1
16.7%
9 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 2
20.0%
0 2
20.0%
3 1
 
10.0%
9 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 2
20.0%
0 2
20.0%
3 1
 
10.0%
9 1
 
10.0%
. 1
 
10.0%

Unnamed: 4
Text

MISSING 

Distinct2
Distinct (%)50.0%
Missing31
Missing (%)88.6%
Memory size412.0 B
2024-02-10T07:04:20.313051image/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%
2024-02-10T07:04:21.219000image/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 

Distinct27
Distinct (%)81.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T07:04:22.243855image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length3.7575758
Min length1

Characters and Unicode

Total characters124
Distinct characters15
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique24 ?
Unique (%)72.7%

Sample

1st row합 계
2nd row171,688
3rd row397,959
4th row779
5th row152
ValueCountFrequency (%)
0 5
 
14.7%
1,221 2
 
5.9%
152 2
 
5.9%
1,630 1
 
2.9%
1,682 1
 
2.9%
397,682 1
 
2.9%
171,641 1
 
2.9%
57 1
 
2.9%
277 1
 
2.9%
47 1
 
2.9%
Other values (18) 18
52.9%
2024-02-10T07:04:24.717960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 22
17.7%
2 15
12.1%
, 14
11.3%
7 13
10.5%
0 10
8.1%
9 10
8.1%
3 8
 
6.5%
5 7
 
5.6%
8 7
 
5.6%
6 6
 
4.8%
Other values (5) 12
9.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 103
83.1%
Other Punctuation 14
 
11.3%
Dash Punctuation 3
 
2.4%
Space Separator 2
 
1.6%
Other Letter 2
 
1.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 22
21.4%
2 15
14.6%
7 13
12.6%
0 10
9.7%
9 10
9.7%
3 8
 
7.8%
5 7
 
6.8%
8 7
 
6.8%
6 6
 
5.8%
4 5
 
4.9%
Other Letter
ValueCountFrequency (%)
합 1
50.0%
계 1
50.0%
Other Punctuation
ValueCountFrequency (%)
, 14
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 122
98.4%
Hangul 2
 
1.6%

Most frequent character per script

Common
ValueCountFrequency (%)
1 22
18.0%
2 15
12.3%
, 14
11.5%
7 13
10.7%
0 10
8.2%
9 10
8.2%
3 8
 
6.6%
5 7
 
5.7%
8 7
 
5.7%
6 6
 
4.9%
Other values (3) 10
8.2%
Hangul
ValueCountFrequency (%)
합 1
50.0%
계 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 122
98.4%
Hangul 2
 
1.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 22
18.0%
2 15
12.3%
, 14
11.5%
7 13
10.7%
0 10
8.2%
9 10
8.2%
3 8
 
6.6%
5 7
 
5.7%
8 7
 
5.7%
6 6
 
4.9%
Other values (3) 10
8.2%
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
2024-02-10T07:04:25.354883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.1818182
Min length1

Characters and Unicode

Total characters72
Distinct characters15
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique21 ?
Unique (%)63.6%

Sample

1st row송정1동
2nd row4,807
3rd row10,456
4th row41
5th row1
ValueCountFrequency (%)
0 8
24.2%
41 2
 
6.1%
17 2
 
6.1%
1 2
 
6.1%
40 1
 
3.0%
10,456 1
 
3.0%
46 1
 
3.0%
4,796 1
 
3.0%
11 1
 
3.0%
3 1
 
3.0%
Other values (13) 13
39.4%
2024-02-10T07:04:26.898057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 14
19.4%
0 12
16.7%
4 10
13.9%
9 5
 
6.9%
7 5
 
6.9%
2 4
 
5.6%
3 4
 
5.6%
5 4
 
5.6%
, 4
 
5.6%
6 3
 
4.2%
Other values (5) 7
9.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 63
87.5%
Other Punctuation 4
 
5.6%
Other Letter 3
 
4.2%
Dash Punctuation 2
 
2.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 14
22.2%
0 12
19.0%
4 10
15.9%
9 5
 
7.9%
7 5
 
7.9%
2 4
 
6.3%
3 4
 
6.3%
5 4
 
6.3%
6 3
 
4.8%
8 2
 
3.2%
Other Letter
ValueCountFrequency (%)
송 1
33.3%
정 1
33.3%
동 1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
1 14
20.3%
0 12
17.4%
4 10
14.5%
9 5
 
7.2%
7 5
 
7.2%
2 4
 
5.8%
3 4
 
5.8%
5 4
 
5.8%
, 4
 
5.8%
6 3
 
4.3%
Other values (2) 4
 
5.8%
Hangul
ValueCountFrequency (%)
송 1
33.3%
정 1
33.3%
동 1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 14
20.3%
0 12
17.4%
4 10
14.5%
9 5
 
7.2%
7 5
 
7.2%
2 4
 
5.8%
3 4
 
5.8%
5 4
 
5.8%
, 4
 
5.8%
6 3
 
4.3%
Other values (2) 4
 
5.8%
Hangul
ValueCountFrequency (%)
송 1
33.3%
정 1
33.3%
동 1
33.3%

Unnamed: 7
Text

MISSING 

Distinct25
Distinct (%)75.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T07:04:27.509064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
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

Unique22 ?
Unique (%)66.7%

Sample

1st row송정2동
2nd row3,422
3rd row6,289
4th row65
5th row9
ValueCountFrequency (%)
0 7
21.2%
26 2
 
6.1%
9 2
 
6.1%
61 1
 
3.0%
27 1
 
3.0%
6,237 1
 
3.0%
3,375 1
 
3.0%
42 1
 
3.0%
52 1
 
3.0%
47 1
 
3.0%
Other values (15) 15
45.5%
2024-02-10T07:04:28.644914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 15
20.5%
0 8
11.0%
3 8
11.0%
6 7
9.6%
4 5
 
6.8%
1 5
 
6.8%
7 5
 
6.8%
9 4
 
5.5%
, 4
 
5.5%
8 3
 
4.1%
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 (%)
2 15
23.8%
0 8
12.7%
3 8
12.7%
6 7
11.1%
4 5
 
7.9%
1 5
 
7.9%
7 5
 
7.9%
9 4
 
6.3%
8 3
 
4.8%
5 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 (%)
2 15
21.4%
0 8
11.4%
3 8
11.4%
6 7
10.0%
4 5
 
7.1%
1 5
 
7.1%
7 5
 
7.1%
9 4
 
5.7%
, 4
 
5.7%
8 3
 
4.3%
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 (%)
2 15
21.4%
0 8
11.4%
3 8
11.4%
6 7
10.0%
4 5
 
7.1%
1 5
 
7.1%
7 5
 
7.1%
9 4
 
5.7%
, 4
 
5.7%
8 3
 
4.3%
Other values (2) 6
 
8.6%
Hangul
ValueCountFrequency (%)
송 1
33.3%
정 1
33.3%
동 1
33.3%

Unnamed: 8
Text

MISSING 

Distinct26
Distinct (%)78.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T07:04:29.053146image/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

Unique23 ?
Unique (%)69.7%

Sample

1st row도산동
2nd row6,648
3rd row14,692
4th row24
5th row3
ValueCountFrequency (%)
0 6
 
18.2%
55 2
 
6.1%
1 2
 
6.1%
3 2
 
6.1%
47 1
 
3.0%
66 1
 
3.0%
14,639 1
 
3.0%
6,636 1
 
3.0%
53 1
 
3.0%
12 1
 
3.0%
Other values (15) 15
45.5%
2024-02-10T07:04:29.861365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 11
15.1%
6 10
13.7%
4 9
12.3%
1 7
9.6%
0 6
8.2%
2 6
8.2%
5 5
6.8%
, 4
 
5.5%
7 4
 
5.5%
9 3
 
4.1%
Other values (5) 8
11.0%

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 (%)
3 11
17.5%
6 10
15.9%
4 9
14.3%
1 7
11.1%
0 6
9.5%
2 6
9.5%
5 5
7.9%
7 4
 
6.3%
9 3
 
4.8%
8 2
 
3.2%
Other Letter
ValueCountFrequency (%)
도 1
33.3%
산 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 (%)
3 11
15.7%
6 10
14.3%
4 9
12.9%
1 7
10.0%
0 6
8.6%
2 6
8.6%
5 5
7.1%
, 4
 
5.7%
7 4
 
5.7%
9 3
 
4.3%
Other values (2) 5
7.1%
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 (%)
3 11
15.7%
6 10
14.3%
4 9
12.9%
1 7
10.0%
0 6
8.6%
2 6
8.6%
5 5
7.1%
, 4
 
5.7%
7 4
 
5.7%
9 3
 
4.3%
Other values (2) 5
7.1%
Hangul
ValueCountFrequency (%)
도 1
33.3%
산 1
33.3%
동 1
33.3%

Unnamed: 9
Text

MISSING 

Distinct23
Distinct (%)69.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T07:04:30.248446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
Mean length1.969697
Min length1

Characters and Unicode

Total characters65
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 row신흥동
2nd row1,983
3rd row4,336
4th row18
5th row3
ValueCountFrequency (%)
0 7
21.2%
9 3
 
9.1%
1 2
 
6.1%
18 2
 
6.1%
3 2
 
6.1%
11 1
 
3.0%
15 1
 
3.0%
1,981 1
 
3.0%
2 1
 
3.0%
4 1
 
3.0%
Other values (12) 12
36.4%
2024-02-10T07:04:31.580101image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 14
21.5%
3 8
12.3%
0 7
10.8%
9 7
10.8%
4 6
9.2%
8 4
 
6.2%
2 4
 
6.2%
, 4
 
6.2%
7 3
 
4.6%
6 2
 
3.1%
Other values (5) 6
9.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 56
86.2%
Other Punctuation 4
 
6.2%
Other Letter 3
 
4.6%
Dash Punctuation 2
 
3.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 14
25.0%
3 8
14.3%
0 7
12.5%
9 7
12.5%
4 6
10.7%
8 4
 
7.1%
2 4
 
7.1%
7 3
 
5.4%
6 2
 
3.6%
5 1
 
1.8%
Other Letter
ValueCountFrequency (%)
신 1
33.3%
흥 1
33.3%
동 1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
1 14
22.6%
3 8
12.9%
0 7
11.3%
9 7
11.3%
4 6
9.7%
8 4
 
6.5%
2 4
 
6.5%
, 4
 
6.5%
7 3
 
4.8%
6 2
 
3.2%
Other values (2) 3
 
4.8%
Hangul
ValueCountFrequency (%)
신 1
33.3%
흥 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 (%)
1 14
22.6%
3 8
12.9%
0 7
11.3%
9 7
11.3%
4 6
9.7%
8 4
 
6.5%
2 4
 
6.5%
, 4
 
6.5%
7 3
 
4.8%
6 2
 
3.2%
Other values (2) 3
 
4.8%
Hangul
ValueCountFrequency (%)
신 1
33.3%
흥 1
33.3%
동 1
33.3%

Unnamed: 10
Text

MISSING 

Distinct24
Distinct (%)70.6%
Missing1
Missing (%)2.9%
Memory size412.0 B
2024-02-10T07:04:32.346337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length3
Mean length2.5294118
Min length1

Characters and Unicode

Total characters86
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

Unique19 ?
Unique (%)55.9%

Sample

1st row출력일자 :
2nd row어룡동
3rd row14,366
4th row33,285
5th row37
ValueCountFrequency (%)
0 7
20.0%
37 2
 
5.7%
8 2
 
5.7%
109 2
 
5.7%
16 2
 
5.7%
1
 
2.9%
14,380 1
 
2.9%
13 1
 
2.9%
14 1
 
2.9%
81 1
 
2.9%
Other values (15) 15
42.9%
2024-02-10T07:04:33.171483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 15
17.4%
0 12
14.0%
3 12
14.0%
8 6
 
7.0%
2 6
 
7.0%
4 6
 
7.0%
9 5
 
5.8%
6 5
 
5.8%
, 4
 
4.7%
5 4
 
4.7%
Other values (10) 11
12.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 73
84.9%
Other Letter 7
 
8.1%
Other Punctuation 5
 
5.8%
Space Separator 1
 
1.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 15
20.5%
0 12
16.4%
3 12
16.4%
8 6
 
8.2%
2 6
 
8.2%
4 6
 
8.2%
9 5
 
6.8%
6 5
 
6.8%
5 4
 
5.5%
7 2
 
2.7%
Other Letter
ValueCountFrequency (%)
어 1
14.3%
룡 1
14.3%
동 1
14.3%
출 1
14.3%
력 1
14.3%
일 1
14.3%
자 1
14.3%
Other Punctuation
ValueCountFrequency (%)
, 4
80.0%
: 1
 
20.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 79
91.9%
Hangul 7
 
8.1%

Most frequent character per script

Common
ValueCountFrequency (%)
1 15
19.0%
0 12
15.2%
3 12
15.2%
8 6
 
7.6%
2 6
 
7.6%
4 6
 
7.6%
9 5
 
6.3%
6 5
 
6.3%
, 4
 
5.1%
5 4
 
5.1%
Other values (3) 4
 
5.1%
Hangul
ValueCountFrequency (%)
어 1
14.3%
룡 1
14.3%
동 1
14.3%
출 1
14.3%
력 1
14.3%
일 1
14.3%
자 1
14.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 79
91.9%
Hangul 7
 
8.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 15
19.0%
0 12
15.2%
3 12
15.2%
8 6
 
7.6%
2 6
 
7.6%
4 6
 
7.6%
9 5
 
6.3%
6 5
 
6.3%
, 4
 
5.1%
5 4
 
5.1%
Other values (3) 4
 
5.1%
Hangul
ValueCountFrequency (%)
어 1
14.3%
룡 1
14.3%
동 1
14.3%
출 1
14.3%
력 1
14.3%
일 1
14.3%
자 1
14.3%

Unnamed: 11
Text

MISSING 

Distinct27
Distinct (%)81.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T07:04:33.703303image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length3
Mean length2.4848485
Min length1

Characters and Unicode

Total characters82
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 row우산동
2nd row15,098
3rd row29,414
4th row81
5th row7
ValueCountFrequency (%)
0 6
 
18.2%
7 3
 
9.1%
275 1
 
3.0%
29,381 1
 
3.0%
15,091 1
 
3.0%
1 1
 
3.0%
33 1
 
3.0%
15 1
 
3.0%
85 1
 
3.0%
70 1
 
3.0%
Other values (16) 16
48.5%
2024-02-10T07:04:34.680356image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 17
20.7%
0 11
13.4%
2 11
13.4%
7 7
8.5%
5 7
8.5%
9 5
 
6.1%
8 5
 
6.1%
3 5
 
6.1%
, 4
 
4.9%
4 4
 
4.9%
Other values (5) 6
 
7.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 73
89.0%
Other Punctuation 4
 
4.9%
Other Letter 3
 
3.7%
Dash Punctuation 2
 
2.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 17
23.3%
0 11
15.1%
2 11
15.1%
7 7
9.6%
5 7
9.6%
9 5
 
6.8%
8 5
 
6.8%
3 5
 
6.8%
4 4
 
5.5%
6 1
 
1.4%
Other Letter
ValueCountFrequency (%)
우 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 79
96.3%
Hangul 3
 
3.7%

Most frequent character per script

Common
ValueCountFrequency (%)
1 17
21.5%
0 11
13.9%
2 11
13.9%
7 7
8.9%
5 7
8.9%
9 5
 
6.3%
8 5
 
6.3%
3 5
 
6.3%
, 4
 
5.1%
4 4
 
5.1%
Other values (2) 3
 
3.8%
Hangul
ValueCountFrequency (%)
우 1
33.3%
산 1
33.3%
동 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 79
96.3%
Hangul 3
 
3.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 17
21.5%
0 11
13.9%
2 11
13.9%
7 7
8.9%
5 7
8.9%
9 5
 
6.3%
8 5
 
6.3%
3 5
 
6.3%
, 4
 
5.1%
4 4
 
5.1%
Other values (2) 3
 
3.8%
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
Minimum2023-10-25 00:00:00
Maximum2023-10-25 00:00:00
2024-02-10T07:04:35.085940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-10T07:04:35.463459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Unnamed: 13
Text

MISSING 

Distinct24
Distinct (%)72.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T07:04:35.947464image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.0909091
Min length1

Characters and Unicode

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

Unique

Unique21 ?
Unique (%)63.6%

Sample

1st row월곡1동
2nd row4,728
3rd row10,078
4th row41
5th row7
ValueCountFrequency (%)
0 7
21.2%
7 3
 
9.1%
9 2
 
6.1%
41 2
 
6.1%
10,078 1
 
3.0%
49 1
 
3.0%
10,041 1
 
3.0%
4,719 1
 
3.0%
2 1
 
3.0%
37 1
 
3.0%
Other values (13) 13
39.4%
2024-02-10T07:04:36.821590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 12
17.4%
1 9
13.0%
4 8
11.6%
7 7
10.1%
3 6
8.7%
9 5
7.2%
5 4
 
5.8%
2 4
 
5.8%
8 4
 
5.8%
, 4
 
5.8%
Other values (5) 6
8.7%

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 (%)
0 12
20.0%
1 9
15.0%
4 8
13.3%
7 7
11.7%
3 6
10.0%
9 5
8.3%
5 4
 
6.7%
2 4
 
6.7%
8 4
 
6.7%
6 1
 
1.7%
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 66
95.7%
Hangul 3
 
4.3%

Most frequent character per script

Common
ValueCountFrequency (%)
0 12
18.2%
1 9
13.6%
4 8
12.1%
7 7
10.6%
3 6
9.1%
9 5
7.6%
5 4
 
6.1%
2 4
 
6.1%
8 4
 
6.1%
, 4
 
6.1%
Other values (2) 3
 
4.5%
Hangul
ValueCountFrequency (%)
월 1
33.3%
곡 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 (%)
0 12
18.2%
1 9
13.6%
4 8
12.1%
7 7
10.6%
3 6
9.1%
9 5
7.6%
5 4
 
6.1%
2 4
 
6.1%
8 4
 
6.1%
, 4
 
6.1%
Other values (2) 3
 
4.5%
Hangul
ValueCountFrequency (%)
월 1
33.3%
곡 1
33.3%
동 1
33.3%

Unnamed: 14
Text

MISSING 

Distinct22
Distinct (%)66.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T07:04:37.194822image/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

Unique18 ?
Unique (%)54.5%

Sample

1st row월곡2동
2nd row6,304
3rd row14,485
4th row29
5th row7
ValueCountFrequency (%)
0 7
21.2%
7 4
 
12.1%
29 2
 
6.1%
56 2
 
6.1%
25 1
 
3.0%
112 1
 
3.0%
14,465 1
 
3.0%
6,300 1
 
3.0%
1 1
 
3.0%
20 1
 
3.0%
Other values (12) 12
36.4%
2024-02-10T07:04:38.095158image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 11
15.1%
4 11
15.1%
2 9
12.3%
5 7
9.6%
1 6
8.2%
6 5
6.8%
7 4
 
5.5%
9 4
 
5.5%
, 4
 
5.5%
3 3
 
4.1%
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 11
17.5%
4 11
17.5%
2 9
14.3%
5 7
11.1%
1 6
9.5%
6 5
7.9%
7 4
 
6.3%
9 4
 
6.3%
3 3
 
4.8%
8 3
 
4.8%
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 70
95.9%
Hangul 3
 
4.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 11
15.7%
4 11
15.7%
2 9
12.9%
5 7
10.0%
1 6
8.6%
6 5
7.1%
7 4
 
5.7%
9 4
 
5.7%
, 4
 
5.7%
3 3
 
4.3%
Other values (2) 6
8.6%
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 11
15.7%
4 11
15.7%
2 9
12.9%
5 7
10.0%
1 6
8.6%
6 5
7.1%
7 4
 
5.7%
9 4
 
5.7%
, 4
 
5.7%
3 3
 
4.3%
Other values (2) 6
8.6%
Hangul
ValueCountFrequency (%)
월 1
33.3%
곡 1
33.3%
동 1
33.3%

Unnamed: 15
Text

MISSING 

Distinct22
Distinct (%)66.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T07:04:38.441143image/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

Unique18 ?
Unique (%)54.5%

Sample

1st row비아동
2nd row3,523
3rd row7,416
4th row27
5th row6
ValueCountFrequency (%)
0 8
24.2%
28 3
 
9.1%
6 2
 
6.1%
9 2
 
6.1%
비아동 1
 
3.0%
3,533 1
 
3.0%
1 1
 
3.0%
10 1
 
3.0%
5 1
 
3.0%
26 1
 
3.0%
Other values (12) 12
36.4%
2024-02-10T07:04:39.422319image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 11
16.9%
2 9
13.8%
3 8
12.3%
6 6
9.2%
1 6
9.2%
5 5
7.7%
, 4
 
6.2%
7 4
 
6.2%
8 3
 
4.6%
9 3
 
4.6%
Other values (4) 6
9.2%

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 (%)
0 11
19.0%
2 9
15.5%
3 8
13.8%
6 6
10.3%
1 6
10.3%
5 5
8.6%
7 4
 
6.9%
8 3
 
5.2%
9 3
 
5.2%
4 3
 
5.2%
Other Letter
ValueCountFrequency (%)
비 1
33.3%
아 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 (%)
0 11
17.7%
2 9
14.5%
3 8
12.9%
6 6
9.7%
1 6
9.7%
5 5
8.1%
, 4
 
6.5%
7 4
 
6.5%
8 3
 
4.8%
9 3
 
4.8%
Hangul
ValueCountFrequency (%)
비 1
33.3%
아 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 (%)
0 11
17.7%
2 9
14.5%
3 8
12.9%
6 6
9.7%
1 6
9.7%
5 5
8.1%
, 4
 
6.5%
7 4
 
6.5%
8 3
 
4.8%
9 3
 
4.8%
Hangul
ValueCountFrequency (%)
비 1
33.3%
아 1
33.3%
동 1
33.3%

Unnamed: 16
Text

MISSING 

Distinct25
Distinct (%)75.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T07:04:39.829076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length4
Mean length2.4848485
Min length1

Characters and Unicode

Total characters82
Distinct characters14
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique22 ?
Unique (%)66.7%

Sample

1st row첨단1동
2nd row11,006
3rd row27,406
4th row22
5th row14
ValueCountFrequency (%)
0 7
21.2%
80 2
 
6.1%
238 2
 
6.1%
126 1
 
3.0%
68 1
 
3.0%
21 1
 
3.0%
27,411 1
 
3.0%
11,024 1
 
3.0%
1 1
 
3.0%
5 1
 
3.0%
Other values (15) 15
45.5%
2024-02-10T07:04:40.787189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 22
26.8%
0 13
15.9%
2 11
13.4%
8 7
 
8.5%
6 5
 
6.1%
3 4
 
4.9%
, 4
 
4.9%
7 4
 
4.9%
4 4
 
4.9%
5 4
 
4.9%
Other values (4) 4
 
4.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 74
90.2%
Other Punctuation 4
 
4.9%
Other Letter 3
 
3.7%
Dash Punctuation 1
 
1.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 22
29.7%
0 13
17.6%
2 11
14.9%
8 7
 
9.5%
6 5
 
6.8%
3 4
 
5.4%
7 4
 
5.4%
4 4
 
5.4%
5 4
 
5.4%
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 79
96.3%
Hangul 3
 
3.7%

Most frequent character per script

Common
ValueCountFrequency (%)
1 22
27.8%
0 13
16.5%
2 11
13.9%
8 7
 
8.9%
6 5
 
6.3%
3 4
 
5.1%
, 4
 
5.1%
7 4
 
5.1%
4 4
 
5.1%
5 4
 
5.1%
Hangul
ValueCountFrequency (%)
첨 1
33.3%
단 1
33.3%
동 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 79
96.3%
Hangul 3
 
3.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 22
27.8%
0 13
16.5%
2 11
13.9%
8 7
 
8.9%
6 5
 
6.3%
3 4
 
5.1%
, 4
 
5.1%
7 4
 
5.1%
4 4
 
5.1%
5 4
 
5.1%
Hangul
ValueCountFrequency (%)
첨 1
33.3%
단 1
33.3%
동 1
33.3%

Unnamed: 17
Text

MISSING 

Distinct26
Distinct (%)78.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T07:04:41.174593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length4
Mean length2.6060606
Min length1

Characters and Unicode

Total characters86
Distinct characters14
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique24 ?
Unique (%)72.7%

Sample

1st row첨단2동
2nd row18,835
3rd row42,178
4th row73
5th row21
ValueCountFrequency (%)
0 7
21.2%
21 2
 
6.1%
194 1
 
3.0%
42,170 1
 
3.0%
18,839 1
 
3.0%
1 1
 
3.0%
8 1
 
3.0%
4 1
 
3.0%
9 1
 
3.0%
157 1
 
3.0%
Other values (16) 16
48.5%
2024-02-10T07:04:42.204449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 16
18.6%
0 13
15.1%
3 10
11.6%
2 8
9.3%
8 8
9.3%
9 7
8.1%
4 7
8.1%
7 5
 
5.8%
, 4
 
4.7%
5 3
 
3.5%
Other values (4) 5
 
5.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 77
89.5%
Other Punctuation 4
 
4.7%
Other Letter 3
 
3.5%
Dash Punctuation 2
 
2.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 16
20.8%
0 13
16.9%
3 10
13.0%
2 8
10.4%
8 8
10.4%
9 7
9.1%
4 7
9.1%
7 5
 
6.5%
5 3
 
3.9%
Other Letter
ValueCountFrequency (%)
첨 1
33.3%
단 1
33.3%
동 1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
1 16
19.3%
0 13
15.7%
3 10
12.0%
2 8
9.6%
8 8
9.6%
9 7
8.4%
4 7
8.4%
7 5
 
6.0%
, 4
 
4.8%
5 3
 
3.6%
Hangul
ValueCountFrequency (%)
첨 1
33.3%
단 1
33.3%
동 1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 16
19.3%
0 13
15.7%
3 10
12.0%
2 8
9.6%
8 8
9.6%
9 7
8.4%
4 7
8.4%
7 5
 
6.0%
, 4
 
4.8%
5 3
 
3.6%
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
2024-02-10T07:04:42.741697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.1515152
Min length1

Characters and Unicode

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

Unique

Unique20 ?
Unique (%)60.6%

Sample

1st row신가동
2nd row7,408
3rd row19,257
4th row42
5th row5
ValueCountFrequency (%)
0 7
21.2%
5 2
 
6.1%
35 2
 
6.1%
42 2
 
6.1%
8 1
 
3.0%
57 1
 
3.0%
19,272 1
 
3.0%
7,415 1
 
3.0%
3 1
 
3.0%
15 1
 
3.0%
Other values (14) 14
42.4%
2024-02-10T07:04:43.705968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 10
14.1%
0 8
11.3%
4 8
11.3%
2 8
11.3%
1 8
11.3%
7 8
11.3%
3 5
7.0%
, 4
 
5.6%
9 3
 
4.2%
6 3
 
4.2%
Other values (5) 6
8.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 63
88.7%
Other Punctuation 4
 
5.6%
Other Letter 3
 
4.2%
Dash Punctuation 1
 
1.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 10
15.9%
0 8
12.7%
4 8
12.7%
2 8
12.7%
1 8
12.7%
7 8
12.7%
3 5
7.9%
9 3
 
4.8%
6 3
 
4.8%
8 2
 
3.2%
Other Letter
ValueCountFrequency (%)
신 1
33.3%
가 1
33.3%
동 1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
5 10
14.7%
0 8
11.8%
4 8
11.8%
2 8
11.8%
1 8
11.8%
7 8
11.8%
3 5
7.4%
, 4
 
5.9%
9 3
 
4.4%
6 3
 
4.4%
Other values (2) 3
 
4.4%
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 (%)
5 10
14.7%
0 8
11.8%
4 8
11.8%
2 8
11.8%
1 8
11.8%
7 8
11.8%
3 5
7.4%
, 4
 
5.9%
9 3
 
4.4%
6 3
 
4.4%
Other values (2) 3
 
4.4%
Hangul
ValueCountFrequency (%)
신 1
33.3%
가 1
33.3%
동 1
33.3%

Unnamed: 19
Text

MISSING 

Distinct25
Distinct (%)75.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T07:04:44.079038image/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

Unique21 ?
Unique (%)63.6%

Sample

1st row운남동
2nd row12,238
3rd row29,636
4th row22
5th row11
ValueCountFrequency (%)
0 6
 
18.2%
81 2
 
6.1%
1 2
 
6.1%
11 2
 
6.1%
65 1
 
3.0%
22 1
 
3.0%
144 1
 
3.0%
29,560 1
 
3.0%
12,231 1
 
3.0%
76 1
 
3.0%
Other values (15) 15
45.5%
2024-02-10T07:04:44.929002image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 16
20.3%
2 12
15.2%
0 9
11.4%
8 6
 
7.6%
6 6
 
7.6%
9 5
 
6.3%
, 4
 
5.1%
3 4
 
5.1%
4 4
 
5.1%
5 4
 
5.1%
Other values (5) 9
11.4%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 16
22.9%
2 12
17.1%
0 9
12.9%
8 6
 
8.6%
6 6
 
8.6%
9 5
 
7.1%
3 4
 
5.7%
4 4
 
5.7%
5 4
 
5.7%
7 4
 
5.7%
Other Letter
ValueCountFrequency (%)
운 1
33.3%
남 1
33.3%
동 1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
1 16
21.1%
2 12
15.8%
0 9
11.8%
8 6
 
7.9%
6 6
 
7.9%
9 5
 
6.6%
, 4
 
5.3%
3 4
 
5.3%
4 4
 
5.3%
5 4
 
5.3%
Other values (2) 6
 
7.9%
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%
2 12
15.8%
0 9
11.8%
8 6
 
7.9%
6 6
 
7.9%
9 5
 
6.6%
, 4
 
5.3%
3 4
 
5.3%
4 4
 
5.3%
5 4
 
5.3%
Other values (2) 6
 
7.9%
Hangul
ValueCountFrequency (%)
운 1
33.3%
남 1
33.3%
동 1
33.3%

Unnamed: 20
Text

MISSING 

Distinct26
Distinct (%)78.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T07:04:45.371982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length3
Mean length2.6969697
Min length1

Characters and Unicode

Total characters89
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 row수완동
2nd row28,353
3rd row75,510
4th row111
5th row21
ValueCountFrequency (%)
0 7
21.2%
1 2
 
6.1%
539 1
 
3.0%
112 1
 
3.0%
75,480 1
 
3.0%
28,354 1
 
3.0%
30 1
 
3.0%
10 1
 
3.0%
176 1
 
3.0%
178 1
 
3.0%
Other values (16) 16
48.5%
2024-02-10T07:04:46.275999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 21
23.6%
0 12
13.5%
5 11
12.4%
2 10
11.2%
7 7
 
7.9%
8 6
 
6.7%
3 6
 
6.7%
, 4
 
4.5%
4 4
 
4.5%
6 2
 
2.2%
Other values (5) 6
 
6.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 81
91.0%
Other Punctuation 4
 
4.5%
Other Letter 3
 
3.4%
Dash Punctuation 1
 
1.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 21
25.9%
0 12
14.8%
5 11
13.6%
2 10
12.3%
7 7
 
8.6%
8 6
 
7.4%
3 6
 
7.4%
4 4
 
4.9%
6 2
 
2.5%
9 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 (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 86
96.6%
Hangul 3
 
3.4%

Most frequent character per script

Common
ValueCountFrequency (%)
1 21
24.4%
0 12
14.0%
5 11
12.8%
2 10
11.6%
7 7
 
8.1%
8 6
 
7.0%
3 6
 
7.0%
, 4
 
4.7%
4 4
 
4.7%
6 2
 
2.3%
Other values (2) 3
 
3.5%
Hangul
ValueCountFrequency (%)
수 1
33.3%
완 1
33.3%
동 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 86
96.6%
Hangul 3
 
3.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 21
24.4%
0 12
14.0%
5 11
12.8%
2 10
11.6%
7 7
 
8.1%
8 6
 
7.0%
3 6
 
7.0%
, 4
 
4.7%
4 4
 
4.7%
6 2
 
2.3%
Other values (2) 3
 
3.5%
Hangul
ValueCountFrequency (%)
수 1
33.3%
완 1
33.3%
동 1
33.3%

Unnamed: 21
Text

MISSING 

Distinct26
Distinct (%)78.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T07:04:46.627321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length3
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

Unique23 ?
Unique (%)69.7%

Sample

1st row하남동
2nd row11,370
3rd row26,775
4th row48
5th row9
ValueCountFrequency (%)
0 6
 
18.2%
72 2
 
6.1%
22 2
 
6.1%
139 1
 
3.0%
270 1
 
3.0%
47 1
 
3.0%
26,797 1
 
3.0%
11,392 1
 
3.0%
1 1
 
3.0%
8 1
 
3.0%
Other values (16) 16
48.5%
2024-02-10T07:04:47.718613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 15
18.5%
2 13
16.0%
7 10
12.3%
0 9
11.1%
3 5
 
6.2%
4 5
 
6.2%
9 5
 
6.2%
, 4
 
4.9%
6 4
 
4.9%
8 4
 
4.9%
Other values (5) 7
8.6%

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 (%)
1 15
20.5%
2 13
17.8%
7 10
13.7%
0 9
12.3%
3 5
 
6.8%
4 5
 
6.8%
9 5
 
6.8%
6 4
 
5.5%
8 4
 
5.5%
5 3
 
4.1%
Other Letter
ValueCountFrequency (%)
하 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 78
96.3%
Hangul 3
 
3.7%

Most frequent character per script

Common
ValueCountFrequency (%)
1 15
19.2%
2 13
16.7%
7 10
12.8%
0 9
11.5%
3 5
 
6.4%
4 5
 
6.4%
9 5
 
6.4%
, 4
 
5.1%
6 4
 
5.1%
8 4
 
5.1%
Other values (2) 4
 
5.1%
Hangul
ValueCountFrequency (%)
하 1
33.3%
남 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 (%)
1 15
19.2%
2 13
16.7%
7 10
12.8%
0 9
11.5%
3 5
 
6.4%
4 5
 
6.4%
9 5
 
6.4%
, 4
 
5.1%
6 4
 
5.1%
8 4
 
5.1%
Other values (2) 4
 
5.1%
Hangul
ValueCountFrequency (%)
하 1
33.3%
남 1
33.3%
동 1
33.3%

Unnamed: 22
Text

MISSING 

Distinct17
Distinct (%)51.5%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T07:04:48.032113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length1
Mean length1.7272727
Min length1

Characters and Unicode

Total characters57
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

Unique10 ?
Unique (%)30.3%

Sample

1st row임곡동
2nd row1,220
3rd row2,010
4th row13
5th row2
ValueCountFrequency (%)
0 8
24.2%
3 4
12.1%
6 4
12.1%
1,220 2
 
6.1%
2 2
 
6.1%
8 2
 
6.1%
7 2
 
6.1%
임곡동 1
 
3.0%
2,010 1
 
3.0%
13 1
 
3.0%
Other values (6) 6
18.2%
2024-02-10T07:04:49.081776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 12
21.1%
1 10
17.5%
2 8
14.0%
3 5
8.8%
6 4
 
7.0%
, 4
 
7.0%
8 3
 
5.3%
7 2
 
3.5%
- 2
 
3.5%
9 2
 
3.5%
Other values (5) 5
8.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 48
84.2%
Other Punctuation 4
 
7.0%
Other Letter 3
 
5.3%
Dash Punctuation 2
 
3.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 12
25.0%
1 10
20.8%
2 8
16.7%
3 5
10.4%
6 4
 
8.3%
8 3
 
6.2%
7 2
 
4.2%
9 2
 
4.2%
4 1
 
2.1%
5 1
 
2.1%
Other Letter
ValueCountFrequency (%)
임 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 54
94.7%
Hangul 3
 
5.3%

Most frequent character per script

Common
ValueCountFrequency (%)
0 12
22.2%
1 10
18.5%
2 8
14.8%
3 5
9.3%
6 4
 
7.4%
, 4
 
7.4%
8 3
 
5.6%
7 2
 
3.7%
- 2
 
3.7%
9 2
 
3.7%
Other values (2) 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 (%)
0 12
22.2%
1 10
18.5%
2 8
14.8%
3 5
9.3%
6 4
 
7.4%
, 4
 
7.4%
8 3
 
5.6%
7 2
 
3.7%
- 2
 
3.7%
9 2
 
3.7%
Other values (2) 2
 
3.7%
Hangul
ValueCountFrequency (%)
임 1
33.3%
곡 1
33.3%
동 1
33.3%

Unnamed: 23
Categorical

Distinct13
Distinct (%)37.1%
Missing0
Missing (%)0.0%
Memory size412.0 B
0
14 
5
3 
<NA>
2 
977
2 
1,724
2 
Other values (8)
12 

Length

Max length5
Median length1
Mean length1.6
Min length1

Unique

Unique4 ?
Unique (%)11.4%

Sample

1st row<NA>
2nd row<NA>
3rd row동곡동
4th row977
5th row1,724

Common Values

ValueCountFrequency (%)
0 14
40.0%
5 3
 
8.6%
<NA> 2
 
5.7%
977 2
 
5.7%
1,724 2
 
5.7%
4 2
 
5.7%
7 2
 
5.7%
3 2
 
5.7%
2 2
 
5.7%
동곡동 1
 
2.9%
Other values (3) 3
 
8.6%

Length

2024-02-10T07:04:49.573971image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
0 14
40.0%
5 3
 
8.6%
na 2
 
5.7%
977 2
 
5.7%
1,724 2
 
5.7%
4 2
 
5.7%
7 2
 
5.7%
3 2
 
5.7%
2 2
 
5.7%
동곡동 1
 
2.9%
Other values (3) 3
 
8.6%

Unnamed: 24
Text

MISSING 

Distinct24
Distinct (%)72.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T07:04:50.026179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length2
Mean length2.030303
Min length1

Characters and Unicode

Total characters67
Distinct characters14
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique21 ?
Unique (%)63.6%

Sample

1st row평동
2nd row2,987
3rd row4,940
4th row13
5th row3
ValueCountFrequency (%)
0 7
21.2%
3 3
 
9.1%
24 2
 
6.1%
17 1
 
3.0%
13 1
 
3.0%
32 1
 
3.0%
4,965 1
 
3.0%
2,985 1
 
3.0%
1 1
 
3.0%
25 1
 
3.0%
Other values (14) 14
42.4%
2024-02-10T07:04:50.846539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

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

Most occurring categories

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

Most frequent character per category

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

Most occurring scripts

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

Most frequent character per script

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

Unnamed: 25
Text

MISSING 

Distinct19
Distinct (%)57.6%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T07:04:51.180936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length1
Mean length1.7575758
Min length1

Characters and Unicode

Total characters58
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 row삼도동
2nd row1,333
3rd row2,156
4th row6
5th row0
ValueCountFrequency (%)
0 9
27.3%
7 5
15.2%
4 4
12.1%
6 2
 
6.1%
삼도동 1
 
3.0%
14 1
 
3.0%
2,149 1
 
3.0%
1,321 1
 
3.0%
1 1
 
3.0%
12 1
 
3.0%
Other values (7) 7
21.2%
2024-02-10T07:04:52.573905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 11
19.0%
0 9
15.5%
4 6
10.3%
7 5
8.6%
3 5
8.6%
2 5
8.6%
, 4
 
6.9%
6 3
 
5.2%
5 3
 
5.2%
- 3
 
5.2%
Other values (4) 4
 
6.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 48
82.8%
Other Punctuation 4
 
6.9%
Dash Punctuation 3
 
5.2%
Other Letter 3
 
5.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 11
22.9%
0 9
18.8%
4 6
12.5%
7 5
10.4%
3 5
10.4%
2 5
10.4%
6 3
 
6.2%
5 3
 
6.2%
9 1
 
2.1%
Other Letter
ValueCountFrequency (%)
삼 1
33.3%
도 1
33.3%
동 1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
1 11
20.0%
0 9
16.4%
4 6
10.9%
7 5
9.1%
3 5
9.1%
2 5
9.1%
, 4
 
7.3%
6 3
 
5.5%
5 3
 
5.5%
- 3
 
5.5%
Hangul
ValueCountFrequency (%)
삼 1
33.3%
도 1
33.3%
동 1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 11
20.0%
0 9
16.4%
4 6
10.9%
7 5
9.1%
3 5
9.1%
2 5
9.1%
, 4
 
7.3%
6 3
 
5.5%
5 3
 
5.5%
- 3
 
5.5%
Hangul
ValueCountFrequency (%)
삼 1
33.3%
도 1
33.3%
동 1
33.3%

Unnamed: 26
Categorical

Distinct15
Distinct (%)42.9%
Missing0
Missing (%)0.0%
Memory size412.0 B
0
12 
3
3 
5
3 
<NA>
2 
1,894
2 
Other values (10)
13 

Length

Max length5
Median length1
Mean length1.7714286
Min length1

Unique

Unique7 ?
Unique (%)20.0%

Sample

1st row<NA>
2nd row<NA>
3rd row본량동
4th row1,164
5th row1,894

Common Values

ValueCountFrequency (%)
0 12
34.3%
3 3
 
8.6%
5 3
 
8.6%
<NA> 2
 
5.7%
1,894 2
 
5.7%
2 2
 
5.7%
8 2
 
5.7%
1 2
 
5.7%
본량동 1
 
2.9%
1,164 1
 
2.9%
Other values (5) 5
14.3%

Length

2024-02-10T07:04:53.096156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
0 12
34.3%
3 4
 
11.4%
5 3
 
8.6%
na 2
 
5.7%
1,894 2
 
5.7%
2 2
 
5.7%
8 2
 
5.7%
1 2
 
5.7%
본량동 1
 
2.9%
1,164 1
 
2.9%
Other values (4) 4
 
11.4%

Unnamed: 27
Text

MISSING 

Distinct25
Distinct (%)75.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T07:04:53.483849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length3
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

Unique22 ?
Unique (%)66.7%

Sample

1st row신창동
2nd row13,918
3rd row34,022
4th row63
5th row11
ValueCountFrequency (%)
0 6
18.2%
11 3
 
9.1%
85 2
 
6.1%
2 2
 
6.1%
133 1
 
3.0%
144 1
 
3.0%
34,010 1
 
3.0%
13,911 1
 
3.0%
12 1
 
3.0%
7 1
 
3.0%
Other values (14) 14
42.4%
2024-02-10T07:04:54.629022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 19
22.9%
0 10
12.0%
2 9
10.8%
3 9
10.8%
8 5
 
6.0%
7 5
 
6.0%
6 5
 
6.0%
, 4
 
4.8%
9 4
 
4.8%
4 4
 
4.8%
Other values (5) 9
10.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 73
88.0%
Other Punctuation 4
 
4.8%
Dash Punctuation 3
 
3.6%
Other Letter 3
 
3.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 19
26.0%
0 10
13.7%
2 9
12.3%
3 9
12.3%
8 5
 
6.8%
7 5
 
6.8%
6 5
 
6.8%
9 4
 
5.5%
4 4
 
5.5%
5 3
 
4.1%
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 80
96.4%
Hangul 3
 
3.6%

Most frequent character per script

Common
ValueCountFrequency (%)
1 19
23.8%
0 10
12.5%
2 9
11.2%
3 9
11.2%
8 5
 
6.2%
7 5
 
6.2%
6 5
 
6.2%
, 4
 
5.0%
9 4
 
5.0%
4 4
 
5.0%
Other values (2) 6
 
7.5%
Hangul
ValueCountFrequency (%)
신 1
33.3%
창 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 19
23.8%
0 10
12.5%
2 9
11.2%
3 9
11.2%
8 5
 
6.2%
7 5
 
6.2%
6 5
 
6.2%
, 4
 
5.0%
9 4
 
5.0%
4 4
 
5.0%
Other values (2) 6
 
7.5%
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>2023.10.25<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
1<NA>작성기준 :<NA>2023.09 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>171,6884,8073,4226,6481,98314,36615,098<NA>4,7286,3043,52311,00618,8357,40812,23828,35311,3701,2209772,9871,3331,16413,918
4<NA>전월말인구수<NA><NA><NA>397,95910,4566,28914,6924,33633,28529,414<NA>10,07814,4857,41627,40642,17819,25729,63675,51026,7752,0101,7244,9402,1561,89434,022
5<NA>전월말거주불명자수<NA><NA><NA>779416524183781<NA>4129272273422211148130136363
6<NA>전월말재외국민등록자수<NA><NA><NA>152193387<NA>77614215112192430011
7<NA>증 가 요 인전 입계<NA>3,09981609337245243<NA>5692702383801341805082911112831512258
8<NA><NA><NA>남자<NA>1,58242315523130126<NA>25483411520072812371668742117122
9<NA><NA><NA>여자<NA>1,51739293814115117<NA>3144361231806299271125354145136
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>540431000<NA>000000000600400
26<NA><NA>국외<NA><NA>0000000<NA>000000000000000
27<NA><NA>기타<NA><NA>0000000<NA>000000000000000
28<NA>세대수증감<NA><NA><NA>-47-11-47-12-214-7<NA>-9-4101847-712200-2-12-3-7
29<NA>인구수증감<NA><NA><NA>-277-17-52-53-913-33<NA>-37-2095-815-76-3022-12025-70-12
30<NA>거주불명자수증감<NA><NA><NA>-570-42-1001<NA>2-11-1-1-311-1-60-1-40-2
31<NA>금월말세대수<NA><NA><NA>171,6414,7963,3756,6361,98114,38015,091<NA>4,7196,3003,53311,02418,8397,41512,23128,35411,3921,2209772,9851,3211,16113,911
32<NA>금월말인구수<NA><NA><NA>397,68210,4396,23714,6394,32733,29829,381<NA>10,04114,4657,42527,41142,17019,27229,56075,48026,7971,9981,7244,9652,1491,89434,010
33<NA>금월말거주불명자수<NA><NA><NA>722412323183782<NA>432828217239231124770122361
34<NA>금월말재외국민등록자수<NA><NA><NA>152193387<NA>776152151119102430011

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