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

Description2022-11-03
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: 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 06:46:32.878250
Analysis finished2024-02-10 06:46:34.234185
Duration1.36 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
2024-02-10T06:46:34.476514image/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%
2024-02-10T06:46:35.671113image/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
2024-02-10T06:46:36.033466image/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%
2024-02-10T06:46:36.985449image/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
2024-02-10T06:46:37.528174image/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 row2022.09 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%
2022.09 1
7.1%
현재 1
7.1%
2024-02-10T06:46:38.471007image/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%
0 2
 
4.8%
여 2
 
4.8%
내 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%
0 2
33.3%
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 3
30.0%
0 2
20.0%
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 3
30.0%
0 2
20.0%
9 1
 
10.0%
. 1
 
10.0%

Unnamed: 4
Text

MISSING 

Distinct2
Distinct (%)50.0%
Missing31
Missing (%)88.6%
Memory size412.0 B
2024-02-10T06:46:38.802656image/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%
2024-02-10T06:46:39.544471image/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
2024-02-10T06:46:40.254402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length3.969697
Min length1

Characters and Unicode

Total characters131
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 row170,702
3rd row402,034
4th row956
5th row141
ValueCountFrequency (%)
0 5
 
14.7%
1,475 2
 
5.9%
1,804 1
 
2.9%
1,976 1
 
2.9%
679 1
 
2.9%
401,729 1
 
2.9%
170,805 1
 
2.9%
277 1
 
2.9%
305 1
 
2.9%
103 1
 
2.9%
Other values (19) 19
55.9%
2024-02-10T06:46:41.700927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 24
18.3%
1 20
15.3%
, 16
12.2%
7 15
11.5%
2 9
 
6.9%
5 8
 
6.1%
4 7
 
5.3%
3 7
 
5.3%
8 7
 
5.3%
9 6
 
4.6%
Other values (5) 12
9.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 109
83.2%
Other Punctuation 16
 
12.2%
Space Separator 2
 
1.5%
Dash Punctuation 2
 
1.5%
Other Letter 2
 
1.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 24
22.0%
1 20
18.3%
7 15
13.8%
2 9
 
8.3%
5 8
 
7.3%
4 7
 
6.4%
3 7
 
6.4%
8 7
 
6.4%
9 6
 
5.5%
6 6
 
5.5%
Other Letter
ValueCountFrequency (%)
합 1
50.0%
계 1
50.0%
Other Punctuation
ValueCountFrequency (%)
, 16
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 129
98.5%
Hangul 2
 
1.5%

Most frequent character per script

Common
ValueCountFrequency (%)
0 24
18.6%
1 20
15.5%
, 16
12.4%
7 15
11.6%
2 9
 
7.0%
5 8
 
6.2%
4 7
 
5.4%
3 7
 
5.4%
8 7
 
5.4%
9 6
 
4.7%
Other values (3) 10
7.8%
Hangul
ValueCountFrequency (%)
합 1
50.0%
계 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 129
98.5%
Hangul 2
 
1.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 24
18.6%
1 20
15.5%
, 16
12.4%
7 15
11.6%
2 9
 
7.0%
5 8
 
6.2%
4 7
 
5.4%
3 7
 
5.4%
8 7
 
5.4%
9 6
 
4.7%
Other values (3) 10
7.8%
Hangul
ValueCountFrequency (%)
합 1
50.0%
계 1
50.0%

Unnamed: 6
Text

MISSING 

Distinct24
Distinct (%)72.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T06:46:42.291077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.3636364
Min length1

Characters and Unicode

Total characters78
Distinct characters14
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique20 ?
Unique (%)60.6%

Sample

1st row송정1동
2nd row4,868
3rd row10,733
4th row76
5th row1
ValueCountFrequency (%)
0 5
 
15.2%
1 4
 
12.1%
66 2
 
6.1%
24 2
 
6.1%
34 1
 
3.0%
76 1
 
3.0%
73 1
 
3.0%
10,622 1
 
3.0%
4,806 1
 
3.0%
50 1
 
3.0%
Other values (14) 14
42.4%
2024-02-10T06:46:43.898682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 15
19.2%
0 10
12.8%
6 10
12.8%
4 8
10.3%
2 7
9.0%
3 7
9.0%
5 4
 
5.1%
8 4
 
5.1%
, 4
 
5.1%
7 3
 
3.8%
Other values (4) 6
 
7.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 68
87.2%
Other Punctuation 4
 
5.1%
Dash Punctuation 3
 
3.8%
Other Letter 3
 
3.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 15
22.1%
0 10
14.7%
6 10
14.7%
4 8
11.8%
2 7
10.3%
3 7
10.3%
5 4
 
5.9%
8 4
 
5.9%
7 3
 
4.4%
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 75
96.2%
Hangul 3
 
3.8%

Most frequent character per script

Common
ValueCountFrequency (%)
1 15
20.0%
0 10
13.3%
6 10
13.3%
4 8
10.7%
2 7
9.3%
3 7
9.3%
5 4
 
5.3%
8 4
 
5.3%
, 4
 
5.3%
7 3
 
4.0%
Hangul
ValueCountFrequency (%)
송 1
33.3%
정 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 10
13.3%
6 10
13.3%
4 8
10.7%
2 7
9.3%
3 7
9.3%
5 4
 
5.3%
8 4
 
5.3%
, 4
 
5.3%
7 3
 
4.0%
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
2024-02-10T06:46:44.482337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
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

Unique22 ?
Unique (%)66.7%

Sample

1st row송정2동
2nd row3,490
3rd row6,430
4th row128
5th row6
ValueCountFrequency (%)
0 5
 
15.2%
6 4
 
12.1%
19 2
 
6.1%
1 1
 
3.0%
49 1
 
3.0%
6,348 1
 
3.0%
3,434 1
 
3.0%
68 1
 
3.0%
82 1
 
3.0%
56 1
 
3.0%
Other values (15) 15
45.5%
2024-02-10T06:46:45.501035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4 10
13.5%
0 9
12.2%
6 9
12.2%
3 9
12.2%
9 6
8.1%
2 6
8.1%
8 5
6.8%
1 4
 
5.4%
, 4
 
5.4%
7 3
 
4.1%
Other values (5) 9
12.2%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 10
15.6%
0 9
14.1%
6 9
14.1%
3 9
14.1%
9 6
9.4%
2 6
9.4%
8 5
7.8%
1 4
 
6.2%
7 3
 
4.7%
5 3
 
4.7%
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 71
95.9%
Hangul 3
 
4.1%

Most frequent character per script

Common
ValueCountFrequency (%)
4 10
14.1%
0 9
12.7%
6 9
12.7%
3 9
12.7%
9 6
8.5%
2 6
8.5%
8 5
7.0%
1 4
 
5.6%
, 4
 
5.6%
7 3
 
4.2%
Other values (2) 6
8.5%
Hangul
ValueCountFrequency (%)
송 1
33.3%
정 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 (%)
4 10
14.1%
0 9
12.7%
6 9
12.7%
3 9
12.7%
9 6
8.5%
2 6
8.5%
8 5
7.0%
1 4
 
5.6%
, 4
 
5.6%
7 3
 
4.2%
Other values (2) 6
8.5%
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
2024-02-10T06:46:45.925617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.2727273
Min length1

Characters and Unicode

Total characters75
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 row6,651
3rd row14,996
4th row32
5th row4
ValueCountFrequency (%)
0 6
 
18.2%
40 2
 
6.1%
11 2
 
6.1%
4 2
 
6.1%
70 1
 
3.0%
82 1
 
3.0%
14,981 1
 
3.0%
6,668 1
 
3.0%
15 1
 
3.0%
17 1
 
3.0%
Other values (15) 15
45.5%
2024-02-10T06:46:46.755260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 14
18.7%
0 9
12.0%
4 9
12.0%
6 7
9.3%
7 6
8.0%
8 6
8.0%
5 5
 
6.7%
2 5
 
6.7%
, 4
 
5.3%
9 3
 
4.0%
Other values (5) 7
9.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 66
88.0%
Other Punctuation 4
 
5.3%
Other Letter 3
 
4.0%
Dash Punctuation 2
 
2.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 14
21.2%
0 9
13.6%
4 9
13.6%
6 7
10.6%
7 6
9.1%
8 6
9.1%
5 5
 
7.6%
2 5
 
7.6%
9 3
 
4.5%
3 2
 
3.0%
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 72
96.0%
Hangul 3
 
4.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 14
19.4%
0 9
12.5%
4 9
12.5%
6 7
9.7%
7 6
8.3%
8 6
8.3%
5 5
 
6.9%
2 5
 
6.9%
, 4
 
5.6%
9 3
 
4.2%
Other values (2) 4
 
5.6%
Hangul
ValueCountFrequency (%)
도 1
33.3%
산 1
33.3%
동 1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 14
19.4%
0 9
12.5%
4 9
12.5%
6 7
9.7%
7 6
8.3%
8 6
8.3%
5 5
 
6.9%
2 5
 
6.9%
, 4
 
5.6%
9 3
 
4.2%
Other values (2) 4
 
5.6%
Hangul
ValueCountFrequency (%)
도 1
33.3%
산 1
33.3%
동 1
33.3%

Unnamed: 9
Text

MISSING 

Distinct20
Distinct (%)60.6%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T06:46:47.124498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
Mean length2.030303
Min length1

Characters and Unicode

Total characters67
Distinct characters15
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique15 ?
Unique (%)45.5%

Sample

1st row신흥동
2nd row2,036
3rd row4,484
4th row16
5th row3
ValueCountFrequency (%)
0 9
27.3%
3 3
 
9.1%
23 3
 
9.1%
29 2
 
6.1%
16 2
 
6.1%
13 2
 
6.1%
2,036 1
 
3.0%
46 1
 
3.0%
4,484 1
 
3.0%
10 1
 
3.0%
Other values (8) 8
24.2%
2024-02-10T06:46:48.370250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 12
17.9%
3 11
16.4%
2 10
14.9%
1 7
10.4%
4 6
9.0%
6 4
 
6.0%
8 4
 
6.0%
, 4
 
6.0%
9 2
 
3.0%
- 2
 
3.0%
Other values (5) 5
7.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 58
86.6%
Other Punctuation 4
 
6.0%
Other Letter 3
 
4.5%
Dash Punctuation 2
 
3.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 12
20.7%
3 11
19.0%
2 10
17.2%
1 7
12.1%
4 6
10.3%
6 4
 
6.9%
8 4
 
6.9%
9 2
 
3.4%
5 1
 
1.7%
7 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 (%)
- 2
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
0 12
18.8%
3 11
17.2%
2 10
15.6%
1 7
10.9%
4 6
9.4%
6 4
 
6.2%
8 4
 
6.2%
, 4
 
6.2%
9 2
 
3.1%
- 2
 
3.1%
Other values (2) 2
 
3.1%
Hangul
ValueCountFrequency (%)
신 1
33.3%
흥 1
33.3%
동 1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 12
18.8%
3 11
17.2%
2 10
15.6%
1 7
10.9%
4 6
9.4%
6 4
 
6.2%
8 4
 
6.2%
, 4
 
6.2%
9 2
 
3.1%
- 2
 
3.1%
Other values (2) 2
 
3.1%
Hangul
ValueCountFrequency (%)
신 1
33.3%
흥 1
33.3%
동 1
33.3%

Unnamed: 10
Text

MISSING 

Distinct28
Distinct (%)82.4%
Missing1
Missing (%)2.9%
Memory size412.0 B
2024-02-10T06:46:48.828999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length3
Mean length2.7941176
Min length1

Characters and Unicode

Total characters95
Distinct characters21
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique26 ?
Unique (%)76.5%

Sample

1st row출력일자 :
2nd row어룡동
3rd row14,022
4th row32,689
5th row64
ValueCountFrequency (%)
0 6
 
17.1%
6 2
 
5.7%
110 1
 
2.9%
1
 
2.9%
출력일자 1
 
2.9%
155 1
 
2.9%
33,023 1
 
2.9%
14,160 1
 
2.9%
34 1
 
2.9%
334 1
 
2.9%
Other values (19) 19
54.3%
2024-02-10T06:46:49.830041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 16
16.8%
3 14
14.7%
0 13
13.7%
2 11
11.6%
6 10
10.5%
4 7
7.4%
8 4
 
4.2%
, 4
 
4.2%
5 4
 
4.2%
출 1
 
1.1%
Other values (11) 11
11.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 81
85.3%
Other Letter 7
 
7.4%
Other Punctuation 5
 
5.3%
Space Separator 1
 
1.1%
Dash Punctuation 1
 
1.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 16
19.8%
3 14
17.3%
0 13
16.0%
2 11
13.6%
6 10
12.3%
4 7
8.6%
8 4
 
4.9%
5 4
 
4.9%
7 1
 
1.2%
9 1
 
1.2%
Other Letter
ValueCountFrequency (%)
출 1
14.3%
자 1
14.3%
일 1
14.3%
력 1
14.3%
어 1
14.3%
동 1
14.3%
룡 1
14.3%
Other Punctuation
ValueCountFrequency (%)
, 4
80.0%
: 1
 
20.0%
Space Separator
ValueCountFrequency (%)
1
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 88
92.6%
Hangul 7
 
7.4%

Most frequent character per script

Common
ValueCountFrequency (%)
1 16
18.2%
3 14
15.9%
0 13
14.8%
2 11
12.5%
6 10
11.4%
4 7
8.0%
8 4
 
4.5%
, 4
 
4.5%
5 4
 
4.5%
1
 
1.1%
Other values (4) 4
 
4.5%
Hangul
ValueCountFrequency (%)
출 1
14.3%
자 1
14.3%
일 1
14.3%
력 1
14.3%
어 1
14.3%
동 1
14.3%
룡 1
14.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 88
92.6%
Hangul 7
 
7.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 16
18.2%
3 14
15.9%
0 13
14.8%
2 11
12.5%
6 10
11.4%
4 7
8.0%
8 4
 
4.5%
, 4
 
4.5%
5 4
 
4.5%
1
 
1.1%
Other values (4) 4
 
4.5%
Hangul
ValueCountFrequency (%)
출 1
14.3%
자 1
14.3%
일 1
14.3%
력 1
14.3%
어 1
14.3%
동 1
14.3%
룡 1
14.3%

Unnamed: 11
Text

MISSING 

Distinct27
Distinct (%)81.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T06:46:50.393328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length3
Mean length2.5454545
Min length1

Characters and Unicode

Total characters84
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 row15,080
3rd row29,678
4th row78
5th row8
ValueCountFrequency (%)
0 6
 
18.2%
1 2
 
6.1%
8 2
 
6.1%
147 1
 
3.0%
301 1
 
3.0%
29,654 1
 
3.0%
15,074 1
 
3.0%
24 1
 
3.0%
6 1
 
3.0%
19 1
 
3.0%
Other values (16) 16
48.5%
2024-02-10T06:46:51.253711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 16
19.0%
0 11
13.1%
7 8
9.5%
8 7
8.3%
2 6
 
7.1%
6 6
 
7.1%
4 6
 
7.1%
5 5
 
6.0%
9 5
 
6.0%
, 4
 
4.8%
Other values (5) 10
11.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 74
88.1%
Other Punctuation 4
 
4.8%
Dash Punctuation 3
 
3.6%
Other Letter 3
 
3.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 16
21.6%
0 11
14.9%
7 8
10.8%
8 7
9.5%
2 6
 
8.1%
6 6
 
8.1%
4 6
 
8.1%
5 5
 
6.8%
9 5
 
6.8%
3 4
 
5.4%
Other Letter
ValueCountFrequency (%)
우 1
33.3%
산 1
33.3%
동 1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 81
96.4%
Hangul 3
 
3.6%

Most frequent character per script

Common
ValueCountFrequency (%)
1 16
19.8%
0 11
13.6%
7 8
9.9%
8 7
8.6%
2 6
 
7.4%
6 6
 
7.4%
4 6
 
7.4%
5 5
 
6.2%
9 5
 
6.2%
, 4
 
4.9%
Other values (2) 7
8.6%
Hangul
ValueCountFrequency (%)
우 1
33.3%
산 1
33.3%
동 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 81
96.4%
Hangul 3
 
3.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 16
19.8%
0 11
13.6%
7 8
9.9%
8 7
8.6%
2 6
 
7.4%
6 6
 
7.4%
4 6
 
7.4%
5 5
 
6.2%
9 5
 
6.2%
, 4
 
4.9%
Other values (2) 7
8.6%
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
Minimum2022-10-11 00:00:00
Maximum2022-10-11 00:00:00
2024-02-10T06:46:51.695155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-10T06:46:52.179113image/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
2024-02-10T06:46:52.508774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.2727273
Min length1

Characters and Unicode

Total characters75
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 row4,875
3rd row10,509
4th row44
5th row6
ValueCountFrequency (%)
0 6
18.2%
27 2
 
6.1%
47 2
 
6.1%
17 2
 
6.1%
6 2
 
6.1%
26 1
 
3.0%
46 1
 
3.0%
10,466 1
 
3.0%
4,857 1
 
3.0%
43 1
 
3.0%
Other values (14) 14
42.4%
2024-02-10T06:46:53.315340image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4 11
14.7%
0 10
13.3%
7 9
12.0%
6 8
10.7%
1 8
10.7%
2 7
9.3%
, 4
 
5.3%
8 4
 
5.3%
5 4
 
5.3%
- 3
 
4.0%
Other values (5) 7
9.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 65
86.7%
Other Punctuation 4
 
5.3%
Dash Punctuation 3
 
4.0%
Other Letter 3
 
4.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 11
16.9%
0 10
15.4%
7 9
13.8%
6 8
12.3%
1 8
12.3%
2 7
10.8%
8 4
 
6.2%
5 4
 
6.2%
9 2
 
3.1%
3 2
 
3.1%
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 72
96.0%
Hangul 3
 
4.0%

Most frequent character per script

Common
ValueCountFrequency (%)
4 11
15.3%
0 10
13.9%
7 9
12.5%
6 8
11.1%
1 8
11.1%
2 7
9.7%
, 4
 
5.6%
8 4
 
5.6%
5 4
 
5.6%
- 3
 
4.2%
Other values (2) 4
 
5.6%
Hangul
ValueCountFrequency (%)
월 1
33.3%
곡 1
33.3%
동 1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
4 11
15.3%
0 10
13.9%
7 9
12.5%
6 8
11.1%
1 8
11.1%
2 7
9.7%
, 4
 
5.6%
8 4
 
5.6%
5 4
 
5.6%
- 3
 
4.2%
Other values (2) 4
 
5.6%
Hangul
ValueCountFrequency (%)
월 1
33.3%
곡 1
33.3%
동 1
33.3%

Unnamed: 14
Text

MISSING 

Distinct27
Distinct (%)81.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T06:46:53.724882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.2727273
Min length1

Characters and Unicode

Total characters75
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 row월곡2동
2nd row6,533
3rd row15,227
4th row36
5th row8
ValueCountFrequency (%)
0 5
 
15.2%
7 3
 
9.1%
8 2
 
6.1%
5 1
 
3.0%
174 1
 
3.0%
15,149 1
 
3.0%
6,509 1
 
3.0%
78 1
 
3.0%
24 1
 
3.0%
29 1
 
3.0%
Other values (16) 16
48.5%
2024-02-10T06:46:54.569096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 11
14.7%
0 7
9.3%
7 7
9.3%
5 7
9.3%
3 6
8.0%
1 6
8.0%
9 6
8.0%
4 6
8.0%
8 5
6.7%
6 4
 
5.3%
Other values (5) 10
13.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 65
86.7%
Other Punctuation 4
 
5.3%
Dash Punctuation 3
 
4.0%
Other Letter 3
 
4.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 11
16.9%
0 7
10.8%
7 7
10.8%
5 7
10.8%
3 6
9.2%
1 6
9.2%
9 6
9.2%
4 6
9.2%
8 5
7.7%
6 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 72
96.0%
Hangul 3
 
4.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 11
15.3%
0 7
9.7%
7 7
9.7%
5 7
9.7%
3 6
8.3%
1 6
8.3%
9 6
8.3%
4 6
8.3%
8 5
6.9%
6 4
 
5.6%
Other values (2) 7
9.7%
Hangul
ValueCountFrequency (%)
월 1
33.3%
곡 1
33.3%
동 1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 11
15.3%
0 7
9.7%
7 7
9.7%
5 7
9.7%
3 6
8.3%
1 6
8.3%
9 6
8.3%
4 6
8.3%
8 5
6.9%
6 4
 
5.6%
Other values (2) 7
9.7%
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
2024-02-10T06:46:54.950688image/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

Unique17 ?
Unique (%)51.5%

Sample

1st row비아동
2nd row3,550
3rd row7,605
4th row27
5th row5
ValueCountFrequency (%)
0 8
24.2%
33 2
 
6.1%
27 2
 
6.1%
25 2
 
6.1%
24 2
 
6.1%
5 2
 
6.1%
21 1
 
3.0%
78 1
 
3.0%
3,549 1
 
3.0%
1 1
 
3.0%
Other values (11) 11
33.3%
2024-02-10T06:46:55.769053image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 12
17.6%
5 12
17.6%
2 8
11.8%
3 7
10.3%
7 5
7.4%
4 5
7.4%
, 4
 
5.9%
1 4
 
5.9%
6 2
 
2.9%
9 2
 
2.9%
Other values (5) 7
10.3%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 12
20.3%
5 12
20.3%
2 8
13.6%
3 7
11.9%
7 5
8.5%
4 5
8.5%
1 4
 
6.8%
6 2
 
3.4%
9 2
 
3.4%
8 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 (%)
- 2
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
0 12
18.5%
5 12
18.5%
2 8
12.3%
3 7
10.8%
7 5
7.7%
4 5
7.7%
, 4
 
6.2%
1 4
 
6.2%
6 2
 
3.1%
9 2
 
3.1%
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 (%)
0 12
18.5%
5 12
18.5%
2 8
12.3%
3 7
10.8%
7 5
7.7%
4 5
7.7%
, 4
 
6.2%
1 4
 
6.2%
6 2
 
3.1%
9 2
 
3.1%
Other values (2) 4
 
6.2%
Hangul
ValueCountFrequency (%)
비 1
33.3%
아 1
33.3%
동 1
33.3%

Unnamed: 16
Text

MISSING 

Distinct26
Distinct (%)78.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T06:46:56.311646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length4
Mean length2.4242424
Min length1

Characters and Unicode

Total characters80
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 row첨단1동
2nd row10,578
3rd row27,193
4th row27
5th row13
ValueCountFrequency (%)
0 6
 
18.2%
68 2
 
6.1%
5 2
 
6.1%
13 2
 
6.1%
66 1
 
3.0%
98 1
 
3.0%
27,146 1
 
3.0%
10,574 1
 
3.0%
47 1
 
3.0%
4 1
 
3.0%
Other values (15) 15
45.5%
2024-02-10T06:46:57.556338image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 11
13.8%
6 10
12.5%
2 10
12.5%
0 9
11.2%
8 9
11.2%
7 7
8.8%
3 4
 
5.0%
, 4
 
5.0%
5 4
 
5.0%
4 4
 
5.0%
Other values (5) 8
10.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 70
87.5%
Other Punctuation 4
 
5.0%
Dash Punctuation 3
 
3.8%
Other Letter 3
 
3.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 11
15.7%
6 10
14.3%
2 10
14.3%
0 9
12.9%
8 9
12.9%
7 7
10.0%
3 4
 
5.7%
5 4
 
5.7%
4 4
 
5.7%
9 2
 
2.9%
Other Letter
ValueCountFrequency (%)
첨 1
33.3%
단 1
33.3%
동 1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 77
96.2%
Hangul 3
 
3.8%

Most frequent character per script

Common
ValueCountFrequency (%)
1 11
14.3%
6 10
13.0%
2 10
13.0%
0 9
11.7%
8 9
11.7%
7 7
9.1%
3 4
 
5.2%
, 4
 
5.2%
5 4
 
5.2%
4 4
 
5.2%
Other values (2) 5
6.5%
Hangul
ValueCountFrequency (%)
첨 1
33.3%
단 1
33.3%
동 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 77
96.2%
Hangul 3
 
3.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 11
14.3%
6 10
13.0%
2 10
13.0%
0 9
11.7%
8 9
11.7%
7 7
9.1%
3 4
 
5.2%
, 4
 
5.2%
5 4
 
5.2%
4 4
 
5.2%
Other values (2) 5
6.5%
Hangul
ValueCountFrequency (%)
첨 1
33.3%
단 1
33.3%
동 1
33.3%

Unnamed: 17
Text

MISSING 

Distinct29
Distinct (%)87.9%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T06:46:58.008244image/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

Unique28 ?
Unique (%)84.8%

Sample

1st row첨단2동
2nd row18,674
3rd row42,882
4th row75
5th row23
ValueCountFrequency (%)
0 5
 
15.2%
206 1
 
3.0%
259 1
 
3.0%
68 1
 
3.0%
42,761 1
 
3.0%
18,669 1
 
3.0%
7 1
 
3.0%
121 1
 
3.0%
5 1
 
3.0%
6 1
 
3.0%
Other values (19) 19
57.6%
2024-02-10T06:46:58.975432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 17
18.9%
2 16
17.8%
6 9
10.0%
0 8
8.9%
8 7
7.8%
7 6
 
6.7%
5 5
 
5.6%
, 4
 
4.4%
4 4
 
4.4%
3 4
 
4.4%
Other values (5) 10
11.1%

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 17
21.2%
2 16
20.0%
6 9
11.2%
0 8
10.0%
8 7
8.8%
7 6
 
7.5%
5 5
 
6.2%
4 4
 
5.0%
3 4
 
5.0%
9 4
 
5.0%
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 17
19.5%
2 16
18.4%
6 9
10.3%
0 8
9.2%
8 7
8.0%
7 6
 
6.9%
5 5
 
5.7%
, 4
 
4.6%
4 4
 
4.6%
3 4
 
4.6%
Other values (2) 7
8.0%
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 17
19.5%
2 16
18.4%
6 9
10.3%
0 8
9.2%
8 7
8.0%
7 6
 
6.9%
5 5
 
5.7%
, 4
 
4.6%
4 4
 
4.6%
3 4
 
4.6%
Other values (2) 7
8.0%
Hangul
ValueCountFrequency (%)
첨 1
33.3%
단 1
33.3%
동 1
33.3%

Unnamed: 18
Text

MISSING 

Distinct27
Distinct (%)81.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T06:46:59.425668image/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

Unique25 ?
Unique (%)75.8%

Sample

1st row신가동
2nd row7,419
3rd row19,426
4th row40
5th row6
ValueCountFrequency (%)
0 6
 
18.2%
6 2
 
6.1%
70 1
 
3.0%
81 1
 
3.0%
19,455 1
 
3.0%
7,423 1
 
3.0%
9 1
 
3.0%
29 1
 
3.0%
4 1
 
3.0%
11 1
 
3.0%
Other values (17) 17
51.5%
2024-02-10T06:47:00.532036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

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

Most occurring categories

ValueCountFrequency (%)
Decimal Number 65
89.0%
Other Punctuation 4
 
5.5%
Other Letter 3
 
4.1%
Dash Punctuation 1
 
1.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 11
16.9%
0 10
15.4%
9 9
13.8%
4 7
10.8%
5 6
9.2%
2 6
9.2%
7 5
7.7%
3 5
7.7%
6 4
 
6.2%
8 2
 
3.1%
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 70
95.9%
Hangul 3
 
4.1%

Most frequent character per script

Common
ValueCountFrequency (%)
1 11
15.7%
0 10
14.3%
9 9
12.9%
4 7
10.0%
5 6
8.6%
2 6
8.6%
7 5
7.1%
3 5
7.1%
6 4
 
5.7%
, 4
 
5.7%
Other values (2) 3
 
4.3%
Hangul
ValueCountFrequency (%)
신 1
33.3%
가 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 (%)
1 11
15.7%
0 10
14.3%
9 9
12.9%
4 7
10.0%
5 6
8.6%
2 6
8.6%
7 5
7.1%
3 5
7.1%
6 4
 
5.7%
, 4
 
5.7%
Other values (2) 3
 
4.3%
Hangul
ValueCountFrequency (%)
신 1
33.3%
가 1
33.3%
동 1
33.3%

Unnamed: 19
Text

MISSING 

Distinct28
Distinct (%)84.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T06:47:00.962869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length3
Mean length2.5454545
Min length1

Characters and Unicode

Total characters84
Distinct characters14
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique26 ?
Unique (%)78.8%

Sample

1st row운남동
2nd row12,302
3rd row30,341
4th row31
5th row10
ValueCountFrequency (%)
0 5
 
15.2%
10 3
 
9.1%
121 1
 
3.0%
139 1
 
3.0%
30,280 1
 
3.0%
12,284 1
 
3.0%
61 1
 
3.0%
18 1
 
3.0%
8 1
 
3.0%
13 1
 
3.0%
Other values (17) 17
51.5%
2024-02-10T06:47:01.796813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 18
21.4%
0 16
19.0%
2 10
11.9%
8 8
9.5%
3 7
 
8.3%
9 5
 
6.0%
6 4
 
4.8%
, 4
 
4.8%
4 4
 
4.8%
- 3
 
3.6%
Other values (4) 5
 
6.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 74
88.1%
Other Punctuation 4
 
4.8%
Dash Punctuation 3
 
3.6%
Other Letter 3
 
3.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 18
24.3%
0 16
21.6%
2 10
13.5%
8 8
10.8%
3 7
 
9.5%
9 5
 
6.8%
6 4
 
5.4%
4 4
 
5.4%
5 2
 
2.7%
Other Letter
ValueCountFrequency (%)
운 1
33.3%
남 1
33.3%
동 1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 81
96.4%
Hangul 3
 
3.6%

Most frequent character per script

Common
ValueCountFrequency (%)
1 18
22.2%
0 16
19.8%
2 10
12.3%
8 8
9.9%
3 7
 
8.6%
9 5
 
6.2%
6 4
 
4.9%
, 4
 
4.9%
4 4
 
4.9%
- 3
 
3.7%
Hangul
ValueCountFrequency (%)
운 1
33.3%
남 1
33.3%
동 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 81
96.4%
Hangul 3
 
3.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 18
22.2%
0 16
19.8%
2 10
12.3%
8 8
9.9%
3 7
 
8.6%
9 5
 
6.2%
6 4
 
4.9%
, 4
 
4.9%
4 4
 
4.9%
- 3
 
3.7%
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
2024-02-10T06:47:02.161447image/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

Unique26 ?
Unique (%)78.8%

Sample

1st row수완동
2nd row28,241
3rd row76,222
4th row85
5th row15
ValueCountFrequency (%)
0 7
21.2%
328 1
 
3.0%
333 1
 
3.0%
90 1
 
3.0%
76,046 1
 
3.0%
28,206 1
 
3.0%
5 1
 
3.0%
176 1
 
3.0%
35 1
 
3.0%
20 1
 
3.0%
Other values (17) 17
51.5%
2024-02-10T06:47:03.194843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 14
15.6%
0 13
14.4%
6 12
13.3%
3 11
12.2%
1 10
11.1%
8 6
6.7%
, 4
 
4.4%
4 4
 
4.4%
7 4
 
4.4%
5 4
 
4.4%
Other values (5) 8
8.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 81
90.0%
Other Punctuation 4
 
4.4%
Other Letter 3
 
3.3%
Dash Punctuation 2
 
2.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 14
17.3%
0 13
16.0%
6 12
14.8%
3 11
13.6%
1 10
12.3%
8 6
7.4%
4 4
 
4.9%
7 4
 
4.9%
5 4
 
4.9%
9 3
 
3.7%
Other Letter
ValueCountFrequency (%)
수 1
33.3%
완 1
33.3%
동 1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
2 14
16.1%
0 13
14.9%
6 12
13.8%
3 11
12.6%
1 10
11.5%
8 6
6.9%
, 4
 
4.6%
4 4
 
4.6%
7 4
 
4.6%
5 4
 
4.6%
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 87
96.7%
Hangul 3
 
3.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 14
16.1%
0 13
14.9%
6 12
13.8%
3 11
12.6%
1 10
11.5%
8 6
6.9%
, 4
 
4.6%
4 4
 
4.6%
7 4
 
4.6%
5 4
 
4.6%
Other values (2) 5
 
5.7%
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
2024-02-10T06:47:03.603650image/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

Unique23 ?
Unique (%)69.7%

Sample

1st row하남동
2nd row10,795
3rd row26,421
4th row39
5th row8
ValueCountFrequency (%)
0 6
 
18.2%
146 2
 
6.1%
1 2
 
6.1%
8 2
 
6.1%
72 1
 
3.0%
123 1
 
3.0%
38 1
 
3.0%
26,496 1
 
3.0%
10,910 1
 
3.0%
75 1
 
3.0%
Other values (15) 15
45.5%
2024-02-10T06:47:04.414557image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 17
20.7%
0 10
12.2%
6 9
11.0%
2 8
9.8%
8 6
 
7.3%
9 6
 
7.3%
4 5
 
6.1%
7 5
 
6.1%
3 5
 
6.1%
, 4
 
4.9%
Other values (5) 7
8.5%

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 17
23.0%
0 10
13.5%
6 9
12.2%
2 8
10.8%
8 6
 
8.1%
9 6
 
8.1%
4 5
 
6.8%
7 5
 
6.8%
3 5
 
6.8%
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 79
96.3%
Hangul 3
 
3.7%

Most frequent character per script

Common
ValueCountFrequency (%)
1 17
21.5%
0 10
12.7%
6 9
11.4%
2 8
10.1%
8 6
 
7.6%
9 6
 
7.6%
4 5
 
6.3%
7 5
 
6.3%
3 5
 
6.3%
, 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 79
96.3%
Hangul 3
 
3.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 17
21.5%
0 10
12.7%
6 9
11.4%
2 8
10.1%
8 6
 
7.6%
9 6
 
7.6%
4 5
 
6.3%
7 5
 
6.3%
3 5
 
6.3%
, 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 

Distinct21
Distinct (%)63.6%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T06:47:04.911557image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length1
Mean length1.8787879
Min length1

Characters and Unicode

Total characters62
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

Unique15 ?
Unique (%)45.5%

Sample

1st row임곡동
2nd row1,261
3rd row2,088
4th row35
5th row2
ValueCountFrequency (%)
0 7
21.2%
3 3
 
9.1%
2 2
 
6.1%
4 2
 
6.1%
6 2
 
6.1%
9 2
 
6.1%
23 2
 
6.1%
34 1
 
3.0%
7 1
 
3.0%
2,054 1
 
3.0%
Other values (10) 10
30.3%
2024-02-10T06:47:05.763805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 10
16.1%
2 10
16.1%
3 7
11.3%
1 7
11.3%
4 5
8.1%
, 4
 
6.5%
6 3
 
4.8%
9 3
 
4.8%
8 3
 
4.8%
5 3
 
4.8%
Other values (5) 7
11.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 52
83.9%
Other Punctuation 4
 
6.5%
Dash Punctuation 3
 
4.8%
Other Letter 3
 
4.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 10
19.2%
2 10
19.2%
3 7
13.5%
1 7
13.5%
4 5
9.6%
6 3
 
5.8%
9 3
 
5.8%
8 3
 
5.8%
5 3
 
5.8%
7 1
 
1.9%
Other Letter
ValueCountFrequency (%)
임 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 59
95.2%
Hangul 3
 
4.8%

Most frequent character per script

Common
ValueCountFrequency (%)
0 10
16.9%
2 10
16.9%
3 7
11.9%
1 7
11.9%
4 5
8.5%
, 4
 
6.8%
6 3
 
5.1%
9 3
 
5.1%
8 3
 
5.1%
5 3
 
5.1%
Other values (2) 4
 
6.8%
Hangul
ValueCountFrequency (%)
임 1
33.3%
곡 1
33.3%
동 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 59
95.2%
Hangul 3
 
4.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 10
16.9%
2 10
16.9%
3 7
11.9%
1 7
11.9%
4 5
8.5%
, 4
 
6.8%
6 3
 
5.1%
9 3
 
5.1%
8 3
 
5.1%
5 3
 
5.1%
Other values (2) 4
 
6.8%
Hangul
ValueCountFrequency (%)
임 1
33.3%
곡 1
33.3%
동 1
33.3%

Unnamed: 23
Text

MISSING 

Distinct19
Distinct (%)57.6%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T06:47:06.178461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length1
Mean length1.9090909
Min length1

Characters and Unicode

Total characters63
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

Unique14 ?
Unique (%)42.4%

Sample

1st row동곡동
2nd row1,039
3rd row1,823
4th row18
5th row4
ValueCountFrequency (%)
0 7
21.2%
4 5
15.2%
7 3
9.1%
17 3
9.1%
18 2
 
6.1%
1 2
 
6.1%
동곡동 1
 
3.0%
1,039 1
 
3.0%
1,823 1
 
3.0%
10 1
 
3.0%
Other values (7) 7
21.2%
2024-02-10T06:47:07.100711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 17
27.0%
0 11
17.5%
4 6
 
9.5%
7 6
 
9.5%
8 5
 
7.9%
, 4
 
6.3%
- 3
 
4.8%
동 2
 
3.2%
3 2
 
3.2%
9 2
 
3.2%
Other values (3) 5
 
7.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 53
84.1%
Other Punctuation 4
 
6.3%
Dash Punctuation 3
 
4.8%
Other Letter 3
 
4.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 17
32.1%
0 11
20.8%
4 6
 
11.3%
7 6
 
11.3%
8 5
 
9.4%
3 2
 
3.8%
9 2
 
3.8%
2 2
 
3.8%
5 2
 
3.8%
Other Letter
ValueCountFrequency (%)
동 2
66.7%
곡 1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
1 17
28.3%
0 11
18.3%
4 6
 
10.0%
7 6
 
10.0%
8 5
 
8.3%
, 4
 
6.7%
- 3
 
5.0%
3 2
 
3.3%
9 2
 
3.3%
2 2
 
3.3%
Hangul
ValueCountFrequency (%)
동 2
66.7%
곡 1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 17
28.3%
0 11
18.3%
4 6
 
10.0%
7 6
 
10.0%
8 5
 
8.3%
, 4
 
6.7%
- 3
 
5.0%
3 2
 
3.3%
9 2
 
3.3%
2 2
 
3.3%
Hangul
ValueCountFrequency (%)
동 2
66.7%
곡 1
33.3%

Unnamed: 24
Text

MISSING 

Distinct24
Distinct (%)72.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T06:47:07.609927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
Mean length2.1212121
Min length1

Characters and Unicode

Total characters70
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 row2,844
3rd row4,628
4th row16
5th row3
ValueCountFrequency (%)
0 6
18.2%
3 4
 
12.1%
16 3
 
9.1%
11 1
 
3.0%
4,628 1
 
3.0%
23 1
 
3.0%
4,763 1
 
3.0%
2,925 1
 
3.0%
135 1
 
3.0%
81 1
 
3.0%
Other values (13) 13
39.4%
2024-02-10T06:47:08.431109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 12
17.1%
3 10
14.3%
0 8
11.4%
2 8
11.4%
4 7
10.0%
8 7
10.0%
6 6
8.6%
, 4
 
5.7%
5 3
 
4.3%
평 1
 
1.4%
Other values (4) 4
 
5.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 63
90.0%
Other Punctuation 4
 
5.7%
Other Letter 2
 
2.9%
Dash Punctuation 1
 
1.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 12
19.0%
3 10
15.9%
0 8
12.7%
2 8
12.7%
4 7
11.1%
8 7
11.1%
6 6
9.5%
5 3
 
4.8%
9 1
 
1.6%
7 1
 
1.6%
Other Letter
ValueCountFrequency (%)
평 1
50.0%
동 1
50.0%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 68
97.1%
Hangul 2
 
2.9%

Most frequent character per script

Common
ValueCountFrequency (%)
1 12
17.6%
3 10
14.7%
0 8
11.8%
2 8
11.8%
4 7
10.3%
8 7
10.3%
6 6
8.8%
, 4
 
5.9%
5 3
 
4.4%
- 1
 
1.5%
Other values (2) 2
 
2.9%
Hangul
ValueCountFrequency (%)
평 1
50.0%
동 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 68
97.1%
Hangul 2
 
2.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 12
17.6%
3 10
14.7%
0 8
11.8%
2 8
11.8%
4 7
10.3%
8 7
10.3%
6 6
8.8%
, 4
 
5.9%
5 3
 
4.4%
- 1
 
1.5%
Other values (2) 2
 
2.9%
Hangul
ValueCountFrequency (%)
평 1
50.0%
동 1
50.0%

Unnamed: 25
Categorical

Distinct17
Distinct (%)48.6%
Missing0
Missing (%)0.0%
Memory size412.0 B
0
10 
6
5 
4
3 
3
2 
7
2 
Other values (12)
13 

Length

Max length5
Median length1
Mean length1.7714286
Min length1

Unique

Unique11 ?
Unique (%)31.4%

Sample

1st row<NA>
2nd row<NA>
3rd row삼도동
4th row1,325
5th row2,188

Common Values

ValueCountFrequency (%)
0 10
28.6%
6 5
14.3%
4 3
 
8.6%
3 2
 
5.7%
7 2
 
5.7%
<NA> 2
 
5.7%
11 1
 
2.9%
1,328 1
 
2.9%
-3 1
 
2.9%
5 1
 
2.9%
Other values (7) 7
20.0%

Length

2024-02-10T06:47:09.342015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
0 10
28.6%
6 5
14.3%
4 3
 
8.6%
3 3
 
8.6%
7 2
 
5.7%
na 2
 
5.7%
11 1
 
2.9%
1,328 1
 
2.9%
5 1
 
2.9%
2 1
 
2.9%
Other values (6) 6
17.1%

Unnamed: 26
Categorical

Distinct13
Distinct (%)37.1%
Missing0
Missing (%)0.0%
Memory size412.0 B
0
12 
2
7 
5
4 
<NA>
2 
6
2 
Other values (8)
8 

Length

Max length5
Median length1
Mean length1.7142857
Min length1

Unique

Unique8 ?
Unique (%)22.9%

Sample

1st row<NA>
2nd row<NA>
3rd row본량동
4th row1,207
5th row1,965

Common Values

ValueCountFrequency (%)
0 12
34.3%
2 7
20.0%
5 4
 
11.4%
<NA> 2
 
5.7%
6 2
 
5.7%
본량동 1
 
2.9%
1,207 1
 
2.9%
1,965 1
 
2.9%
11 1
 
2.9%
3 1
 
2.9%
Other values (3) 3
 
8.6%

Length

2024-02-10T06:47:09.880436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
0 12
34.3%
2 7
20.0%
5 4
 
11.4%
na 2
 
5.7%
6 2
 
5.7%
본량동 1
 
2.9%
1,207 1
 
2.9%
1,965 1
 
2.9%
11 1
 
2.9%
3 1
 
2.9%
Other values (3) 3
 
8.6%

Unnamed: 27
Text

MISSING 

Distinct28
Distinct (%)84.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T06:47:10.300077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length3
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

Unique26 ?
Unique (%)78.8%

Sample

1st row신창동
2nd row13,912
3rd row34,506
4th row78
5th row10
ValueCountFrequency (%)
0 5
 
15.2%
10 2
 
6.1%
160 1
 
3.0%
34,478 1
 
3.0%
13,924 1
 
3.0%
18 1
 
3.0%
28 1
 
3.0%
12 1
 
3.0%
15 1
 
3.0%
9 1
 
3.0%
Other values (18) 18
54.5%
2024-02-10T06:47:11.294256image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 16
18.4%
0 14
16.1%
3 8
9.2%
2 8
9.2%
4 6
 
6.9%
6 6
 
6.9%
8 6
 
6.9%
9 5
 
5.7%
7 5
 
5.7%
, 4
 
4.6%
Other values (5) 9
10.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 78
89.7%
Other Punctuation 4
 
4.6%
Other Letter 3
 
3.4%
Dash Punctuation 2
 
2.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 16
20.5%
0 14
17.9%
3 8
10.3%
2 8
10.3%
4 6
 
7.7%
6 6
 
7.7%
8 6
 
7.7%
9 5
 
6.4%
7 5
 
6.4%
5 4
 
5.1%
Other Letter
ValueCountFrequency (%)
신 1
33.3%
창 1
33.3%
동 1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
1 16
19.0%
0 14
16.7%
3 8
9.5%
2 8
9.5%
4 6
 
7.1%
6 6
 
7.1%
8 6
 
7.1%
9 5
 
6.0%
7 5
 
6.0%
, 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 16
19.0%
0 14
16.7%
3 8
9.5%
2 8
9.5%
4 6
 
7.1%
6 6
 
7.1%
8 6
 
7.1%
9 5
 
6.0%
7 5
 
6.0%
, 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>2022.10.11<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
1<NA>작성기준 :<NA>2022.09 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>170,7024,8683,4906,6512,03614,02215,080<NA>4,8756,5333,55010,57818,6747,41912,30228,24110,7951,2611,0392,8441,3251,20713,912
4<NA>전월말인구수<NA><NA><NA>402,03410,7336,43014,9964,48432,68929,678<NA>10,50915,2277,60527,19342,88219,42630,34176,22226,4212,0881,8234,6282,1881,96534,506
5<NA>전월말거주불명자수<NA><NA><NA>9567612832166478<NA>4436272775403185393518166578
6<NA>전월말재외국민등록자수<NA><NA><NA>141164368<NA>68513236101582430010
7<NA>증 가 요 인전 입계<NA>3,700737914146641273<NA>66995516833918920046934710171841311280
8<NA><NA><NA>남자<NA>1,89740457423321135<NA>244730811729210823920141010276136
9<NA><NA><NA>여자<NA>1,80333346723320138<NA>425225871679792230146678265144
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>276517080350<NA>17705611800231730015
26<NA><NA>국외<NA><NA>0000000<NA>000000000000000
27<NA><NA>기타<NA><NA>0000000<NA>000000000000000
28<NA>세대수증감<NA><NA><NA>103-62-5617-3138-6<NA>-18-24-1-4-54-18-35115-19-18813212
29<NA>인구수증감<NA><NA><NA>-305-111-82-15-13334-24<NA>-43-78-25-47-12129-61-17675-34-19135-32-28
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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