Overview

Dataset statistics

Number of variables28
Number of observations35
Missing cells205
Missing cells (%)20.9%
Duplicate rows1
Duplicate rows (%)2.9%
Total size in memory7.8 KiB
Average record size in memory228.8 B

Variable types

Unsupported1
Text24
DateTime1
Categorical2

Dataset

Description2023-05-25
Author주민등록인구통계
URLhttps://bigdata.gwangju.go.kr/usr/dataSet/getDataDetailView.rd?dataSetUncd=DS000201924

Alerts

Unnamed: 12 has constant value ""Constant
Dataset has 1 (2.9%) duplicate rowsDuplicates
Unnamed: 0 has 35 (100.0%) missing valuesMissing
인구이동보고서(1호) has 19 (54.3%) missing valuesMissing
Unnamed: 2 has 24 (68.6%) missing valuesMissing
Unnamed: 3 has 23 (65.7%) missing valuesMissing
Unnamed: 4 has 31 (88.6%) missing valuesMissing
Unnamed: 5 has 2 (5.7%) missing valuesMissing
Unnamed: 6 has 2 (5.7%) missing valuesMissing
Unnamed: 7 has 2 (5.7%) missing valuesMissing
Unnamed: 8 has 2 (5.7%) missing valuesMissing
Unnamed: 9 has 2 (5.7%) missing valuesMissing
Unnamed: 10 has 1 (2.9%) missing valuesMissing
Unnamed: 11 has 2 (5.7%) missing valuesMissing
Unnamed: 12 has 34 (97.1%) missing valuesMissing
Unnamed: 13 has 2 (5.7%) missing valuesMissing
Unnamed: 14 has 2 (5.7%) missing valuesMissing
Unnamed: 15 has 2 (5.7%) missing valuesMissing
Unnamed: 16 has 2 (5.7%) missing valuesMissing
Unnamed: 17 has 2 (5.7%) missing valuesMissing
Unnamed: 18 has 2 (5.7%) missing valuesMissing
Unnamed: 19 has 2 (5.7%) missing valuesMissing
Unnamed: 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 06:56:56.215570
Analysis finished2024-02-10 06:56:57.638374
Duration1.42 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
2024-02-10T06:56:58.182282image/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%
2024-02-10T06:56:59.844241image/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
2024-02-10T06:57:00.523416image/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%
2024-02-10T06:57:02.313393image/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
2024-02-10T06:57:02.766922image/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 row2023.04 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%
2023.04 1
7.1%
현재 1
7.1%
2024-02-10T06:57:04.111363image/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%
4 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%
4 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%
4 1
 
10.0%
. 1
 
10.0%

Unnamed: 4
Text

MISSING 

Distinct2
Distinct (%)50.0%
Missing31
Missing (%)88.6%
Memory size412.0 B
2024-02-10T06:57:04.499048image/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%
2024-02-10T06:57:05.304071image/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
2024-02-10T06:57:05.831571image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length3.7272727
Min length1

Characters and Unicode

Total characters123
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

Unique25 ?
Unique (%)75.8%

Sample

1st row합 계
2nd row171,017
3rd row399,149
4th row790
5th row145
ValueCountFrequency (%)
0 4
 
11.8%
1 2
 
5.9%
1,114 2
 
5.9%
1,504 1
 
2.9%
3,255 1
 
2.9%
804 1
 
2.9%
398,941 1
 
2.9%
171,197 1
 
2.9%
14 1
 
2.9%
208 1
 
2.9%
Other values (19) 19
55.9%
2024-02-10T06:57:06.864932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 31
25.2%
0 14
11.4%
, 14
11.4%
7 12
 
9.8%
4 10
 
8.1%
9 10
 
8.1%
5 7
 
5.7%
8 7
 
5.7%
2 5
 
4.1%
3 5
 
4.1%
Other values (5) 8
 
6.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 104
84.6%
Other Punctuation 14
 
11.4%
Space Separator 2
 
1.6%
Other Letter 2
 
1.6%
Dash Punctuation 1
 
0.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 31
29.8%
0 14
13.5%
7 12
 
11.5%
4 10
 
9.6%
9 10
 
9.6%
5 7
 
6.7%
8 7
 
6.7%
2 5
 
4.8%
3 5
 
4.8%
6 3
 
2.9%
Other Letter
ValueCountFrequency (%)
합 1
50.0%
계 1
50.0%
Other Punctuation
ValueCountFrequency (%)
, 14
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 121
98.4%
Hangul 2
 
1.6%

Most frequent character per script

Common
ValueCountFrequency (%)
1 31
25.6%
0 14
11.6%
, 14
11.6%
7 12
 
9.9%
4 10
 
8.3%
9 10
 
8.3%
5 7
 
5.8%
8 7
 
5.8%
2 5
 
4.1%
3 5
 
4.1%
Other values (3) 6
 
5.0%
Hangul
ValueCountFrequency (%)
합 1
50.0%
계 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 121
98.4%
Hangul 2
 
1.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 31
25.6%
0 14
11.6%
, 14
11.6%
7 12
 
9.9%
4 10
 
8.3%
9 10
 
8.3%
5 7
 
5.8%
8 7
 
5.8%
2 5
 
4.1%
3 5
 
4.1%
Other values (3) 6
 
5.0%
Hangul
ValueCountFrequency (%)
합 1
50.0%
계 1
50.0%

Unnamed: 6
Text

MISSING 

Distinct23
Distinct (%)69.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T06:57:07.226659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.1212121
Min length1

Characters and Unicode

Total characters70
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

Unique19 ?
Unique (%)57.6%

Sample

1st row송정1동
2nd row4,804
3rd row10,529
4th row44
5th row1
ValueCountFrequency (%)
0 6
18.2%
1 4
 
12.1%
24 2
 
6.1%
3 2
 
6.1%
44 2
 
6.1%
79 1
 
3.0%
36 1
 
3.0%
10,529 1
 
3.0%
43 1
 
3.0%
4,815 1
 
3.0%
Other values (12) 12
36.4%
2024-02-10T06:57:08.260287image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4 12
17.1%
1 11
15.7%
0 9
12.9%
2 7
10.0%
7 5
7.1%
3 5
7.1%
8 4
 
5.7%
, 4
 
5.7%
9 3
 
4.3%
6 3
 
4.3%
Other values (5) 7
10.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 62
88.6%
Other Punctuation 4
 
5.7%
Other Letter 3
 
4.3%
Dash Punctuation 1
 
1.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 12
19.4%
1 11
17.7%
0 9
14.5%
2 7
11.3%
7 5
8.1%
3 5
8.1%
8 4
 
6.5%
9 3
 
4.8%
6 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 (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 67
95.7%
Hangul 3
 
4.3%

Most frequent character per script

Common
ValueCountFrequency (%)
4 12
17.9%
1 11
16.4%
0 9
13.4%
2 7
10.4%
7 5
7.5%
3 5
7.5%
8 4
 
6.0%
, 4
 
6.0%
9 3
 
4.5%
6 3
 
4.5%
Other values (2) 4
 
6.0%
Hangul
ValueCountFrequency (%)
송 1
33.3%
정 1
33.3%
동 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 67
95.7%
Hangul 3
 
4.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4 12
17.9%
1 11
16.4%
0 9
13.4%
2 7
10.4%
7 5
7.5%
3 5
7.5%
8 4
 
6.0%
, 4
 
6.0%
9 3
 
4.5%
6 3
 
4.5%
Other values (2) 4
 
6.0%
Hangul
ValueCountFrequency (%)
송 1
33.3%
정 1
33.3%
동 1
33.3%

Unnamed: 7
Text

MISSING 

Distinct23
Distinct (%)69.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T06:57:08.660899image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length2.1212121
Min length1

Characters and Unicode

Total characters70
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

Unique19 ?
Unique (%)57.6%

Sample

1st row송정2동
2nd row3,435
3rd row6,319
4th row58
5th row8
ValueCountFrequency (%)
0 8
24.2%
29 2
 
6.1%
8 2
 
6.1%
13 2
 
6.1%
35 2
 
6.1%
17 1
 
3.0%
58 1
 
3.0%
45 1
 
3.0%
66 1
 
3.0%
6,306 1
 
3.0%
Other values (12) 12
36.4%
2024-02-10T06:57:09.500547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 11
15.7%
0 10
14.3%
6 7
10.0%
5 6
8.6%
2 6
8.6%
1 6
8.6%
8 5
7.1%
4 5
7.1%
9 4
 
5.7%
, 4
 
5.7%
Other values (5) 6
8.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 61
87.1%
Other Punctuation 4
 
5.7%
Other Letter 3
 
4.3%
Dash Punctuation 2
 
2.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 11
18.0%
0 10
16.4%
6 7
11.5%
5 6
9.8%
2 6
9.8%
1 6
9.8%
8 5
8.2%
4 5
8.2%
9 4
 
6.6%
7 1
 
1.6%
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 67
95.7%
Hangul 3
 
4.3%

Most frequent character per script

Common
ValueCountFrequency (%)
3 11
16.4%
0 10
14.9%
6 7
10.4%
5 6
9.0%
2 6
9.0%
1 6
9.0%
8 5
7.5%
4 5
7.5%
9 4
 
6.0%
, 4
 
6.0%
Other values (2) 3
 
4.5%
Hangul
ValueCountFrequency (%)
송 1
33.3%
정 1
33.3%
동 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 67
95.7%
Hangul 3
 
4.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 11
16.4%
0 10
14.9%
6 7
10.4%
5 6
9.0%
2 6
9.0%
1 6
9.0%
8 5
7.5%
4 5
7.5%
9 4
 
6.0%
, 4
 
6.0%
Other values (2) 3
 
4.5%
Hangul
ValueCountFrequency (%)
송 1
33.3%
정 1
33.3%
동 1
33.3%

Unnamed: 8
Text

MISSING 

Distinct23
Distinct (%)69.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T06:57:09.887487image/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

Unique19 ?
Unique (%)57.6%

Sample

1st row도산동
2nd row6,640
3rd row14,772
4th row21
5th row3
ValueCountFrequency (%)
0 8
24.2%
38 2
 
6.1%
3 2
 
6.1%
57 2
 
6.1%
21 2
 
6.1%
76 1
 
3.0%
6,641 1
 
3.0%
1 1
 
3.0%
9 1
 
3.0%
68 1
 
3.0%
Other values (12) 12
36.4%
2024-02-10T06:57:10.925497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4 10
14.1%
0 9
12.7%
1 9
12.7%
7 8
11.3%
3 7
9.9%
6 7
9.9%
2 5
7.0%
, 4
 
5.6%
5 3
 
4.2%
8 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 (%)
4 10
15.9%
0 9
14.3%
1 9
14.3%
7 8
12.7%
3 7
11.1%
6 7
11.1%
2 5
7.9%
5 3
 
4.8%
8 3
 
4.8%
9 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 (%)
- 1
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
4 10
14.7%
0 9
13.2%
1 9
13.2%
7 8
11.8%
3 7
10.3%
6 7
10.3%
2 5
7.4%
, 4
 
5.9%
5 3
 
4.4%
8 3
 
4.4%
Other values (2) 3
 
4.4%
Hangul
ValueCountFrequency (%)
도 1
33.3%
산 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 (%)
4 10
14.7%
0 9
13.2%
1 9
13.2%
7 8
11.8%
3 7
10.3%
6 7
10.3%
2 5
7.4%
, 4
 
5.9%
5 3
 
4.4%
8 3
 
4.4%
Other values (2) 3
 
4.4%
Hangul
ValueCountFrequency (%)
도 1
33.3%
산 1
33.3%
동 1
33.3%

Unnamed: 9
Text

MISSING 

Distinct25
Distinct (%)75.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T06:57:11.448032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
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

Unique22 ?
Unique (%)66.7%

Sample

1st row신흥동
2nd row2,014
3rd row4,407
4th row21
5th row3
ValueCountFrequency (%)
0 7
21.2%
10 2
 
6.1%
2 2
 
6.1%
12 2
 
6.1%
3 2
 
6.1%
22 1
 
3.0%
37 1
 
3.0%
4,395 1
 
3.0%
2,009 1
 
3.0%
5 1
 
3.0%
Other values (13) 13
39.4%
2024-02-10T06:57:12.368546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 13
19.4%
1 12
17.9%
2 10
14.9%
4 6
9.0%
3 4
 
6.0%
, 4
 
6.0%
7 3
 
4.5%
6 3
 
4.5%
5 3
 
4.5%
- 3
 
4.5%
Other values (4) 6
9.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 57
85.1%
Other Punctuation 4
 
6.0%
Dash Punctuation 3
 
4.5%
Other Letter 3
 
4.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 13
22.8%
1 12
21.1%
2 10
17.5%
4 6
10.5%
3 4
 
7.0%
7 3
 
5.3%
6 3
 
5.3%
5 3
 
5.3%
9 3
 
5.3%
Other Letter
ValueCountFrequency (%)
신 1
33.3%
흥 1
33.3%
동 1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
0 13
20.3%
1 12
18.8%
2 10
15.6%
4 6
9.4%
3 4
 
6.2%
, 4
 
6.2%
7 3
 
4.7%
6 3
 
4.7%
5 3
 
4.7%
- 3
 
4.7%
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 13
20.3%
1 12
18.8%
2 10
15.6%
4 6
9.4%
3 4
 
6.2%
, 4
 
6.2%
7 3
 
4.7%
6 3
 
4.7%
5 3
 
4.7%
- 3
 
4.7%
Hangul
ValueCountFrequency (%)
신 1
33.3%
흥 1
33.3%
동 1
33.3%

Unnamed: 10
Text

MISSING 

Distinct26
Distinct (%)76.5%
Missing1
Missing (%)2.9%
Memory size412.0 B
2024-02-10T06:57:12.808581image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length3
Mean length2.4411765
Min length1

Characters and Unicode

Total characters83
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

Unique22 ?
Unique (%)64.7%

Sample

1st row출력일자 :
2nd row어룡동
3rd row14,329
4th row33,272
5th row34
ValueCountFrequency (%)
0 6
 
17.1%
4 2
 
5.7%
7 2
 
5.7%
138 2
 
5.7%
출력일자 1
 
2.9%
16 1
 
2.9%
33,228 1
 
2.9%
14,335 1
 
2.9%
44 1
 
2.9%
6 1
 
2.9%
Other values (17) 17
48.6%
2024-02-10T06:57:13.742356image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 12
14.5%
4 9
10.8%
0 8
9.6%
1 8
9.6%
2 8
9.6%
7 6
7.2%
8 6
7.2%
6 6
7.2%
9 5
6.0%
, 4
 
4.8%
Other values (11) 11
13.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 69
83.1%
Other Letter 7
 
8.4%
Other Punctuation 5
 
6.0%
Space Separator 1
 
1.2%
Dash Punctuation 1
 
1.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 12
17.4%
4 9
13.0%
0 8
11.6%
1 8
11.6%
2 8
11.6%
7 6
8.7%
8 6
8.7%
6 6
8.7%
9 5
7.2%
5 1
 
1.4%
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%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 76
91.6%
Hangul 7
 
8.4%

Most frequent character per script

Common
ValueCountFrequency (%)
3 12
15.8%
4 9
11.8%
0 8
10.5%
1 8
10.5%
2 8
10.5%
7 6
7.9%
8 6
7.9%
6 6
7.9%
9 5
6.6%
, 4
 
5.3%
Other values (4) 4
 
5.3%
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 76
91.6%
Hangul 7
 
8.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 12
15.8%
4 9
11.8%
0 8
10.5%
1 8
10.5%
2 8
10.5%
7 6
7.9%
8 6
7.9%
6 6
7.9%
9 5
6.6%
, 4
 
5.3%
Other values (4) 4
 
5.3%
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 

Distinct26
Distinct (%)78.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T06:57:14.198813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length3
Mean length2.5151515
Min length1

Characters and Unicode

Total characters83
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

Unique24 ?
Unique (%)72.7%

Sample

1st row우산동
2nd row14,985
3rd row29,408
4th row91
5th row7
ValueCountFrequency (%)
0 7
21.2%
7 2
 
6.1%
152 1
 
3.0%
29,503 1
 
3.0%
15,074 1
 
3.0%
2 1
 
3.0%
95 1
 
3.0%
89 1
 
3.0%
21 1
 
3.0%
105 1
 
3.0%
Other values (16) 16
48.5%
2024-02-10T06:57:15.081525image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 15
18.1%
9 13
15.7%
1 13
15.7%
2 9
10.8%
5 6
 
7.2%
3 6
 
7.2%
4 5
 
6.0%
8 5
 
6.0%
, 4
 
4.8%
7 3
 
3.6%
Other values (4) 4
 
4.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 76
91.6%
Other Punctuation 4
 
4.8%
Other Letter 3
 
3.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 15
19.7%
9 13
17.1%
1 13
17.1%
2 9
11.8%
5 6
 
7.9%
3 6
 
7.9%
4 5
 
6.6%
8 5
 
6.6%
7 3
 
3.9%
6 1
 
1.3%
Other Letter
ValueCountFrequency (%)
우 1
33.3%
산 1
33.3%
동 1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
0 15
18.8%
9 13
16.2%
1 13
16.2%
2 9
11.2%
5 6
 
7.5%
3 6
 
7.5%
4 5
 
6.2%
8 5
 
6.2%
, 4
 
5.0%
7 3
 
3.8%
Hangul
ValueCountFrequency (%)
우 1
33.3%
산 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 (%)
0 15
18.8%
9 13
16.2%
1 13
16.2%
2 9
11.2%
5 6
 
7.5%
3 6
 
7.5%
4 5
 
6.2%
8 5
 
6.2%
, 4
 
5.0%
7 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
Minimum2023-05-17 00:00:00
Maximum2023-05-17 00:00:00
2024-02-10T06:57:15.597404image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-10T06:57:15.916923image/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
2024-02-10T06:57:16.214220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.2121212
Min length1

Characters and Unicode

Total characters73
Distinct characters15
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique20 ?
Unique (%)60.6%

Sample

1st row월곡1동
2nd row4,767
3rd row10,208
4th row46
5th row7
ValueCountFrequency (%)
0 7
21.2%
39 2
 
6.1%
7 2
 
6.1%
18 2
 
6.1%
4 2
 
6.1%
44 1
 
3.0%
46 1
 
3.0%
70 1
 
3.0%
10,190 1
 
3.0%
4,751 1
 
3.0%
Other values (13) 13
39.4%
2024-02-10T06:57:17.325975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 12
16.4%
1 12
16.4%
4 10
13.7%
7 6
8.2%
9 5
6.8%
8 5
6.8%
3 4
 
5.5%
2 4
 
5.5%
, 4
 
5.5%
6 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 (%)
0 12
19.0%
1 12
19.0%
4 10
15.9%
7 6
9.5%
9 5
7.9%
8 5
7.9%
3 4
 
6.3%
2 4
 
6.3%
6 3
 
4.8%
5 2
 
3.2%
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 70
95.9%
Hangul 3
 
4.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 12
17.1%
1 12
17.1%
4 10
14.3%
7 6
8.6%
9 5
7.1%
8 5
7.1%
3 4
 
5.7%
2 4
 
5.7%
, 4
 
5.7%
6 3
 
4.3%
Other values (2) 5
7.1%
Hangul
ValueCountFrequency (%)
월 1
33.3%
곡 1
33.3%
동 1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 12
17.1%
1 12
17.1%
4 10
14.3%
7 6
8.6%
9 5
7.1%
8 5
7.1%
3 4
 
5.7%
2 4
 
5.7%
, 4
 
5.7%
6 3
 
4.3%
Other values (2) 5
7.1%
Hangul
ValueCountFrequency (%)
월 1
33.3%
곡 1
33.3%
동 1
33.3%

Unnamed: 14
Text

MISSING 

Distinct24
Distinct (%)72.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T06:57:17.694518image/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

Unique20 ?
Unique (%)60.6%

Sample

1st row월곡2동
2nd row6,357
3rd row14,742
4th row35
5th row6
ValueCountFrequency (%)
0 7
21.2%
6 2
 
6.1%
4 2
 
6.1%
35 2
 
6.1%
56 1
 
3.0%
14,742 1
 
3.0%
78 1
 
3.0%
14,698 1
 
3.0%
6,350 1
 
3.0%
44 1
 
3.0%
Other values (14) 14
42.4%
2024-02-10T06:57:18.833874image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4 9
12.5%
0 8
11.1%
3 8
11.1%
5 8
11.1%
6 7
9.7%
2 7
9.7%
1 6
8.3%
7 5
6.9%
, 4
5.6%
9 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 (%)
4 9
14.3%
0 8
12.7%
3 8
12.7%
5 8
12.7%
6 7
11.1%
2 7
11.1%
1 6
9.5%
7 5
7.9%
9 3
 
4.8%
8 2
 
3.2%
Other Letter
ValueCountFrequency (%)
월 1
33.3%
곡 1
33.3%
동 1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
4 9
13.0%
0 8
11.6%
3 8
11.6%
5 8
11.6%
6 7
10.1%
2 7
10.1%
1 6
8.7%
7 5
7.2%
, 4
5.8%
9 3
 
4.3%
Other values (2) 4
5.8%
Hangul
ValueCountFrequency (%)
월 1
33.3%
곡 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 (%)
4 9
13.0%
0 8
11.6%
3 8
11.6%
5 8
11.6%
6 7
10.1%
2 7
10.1%
1 6
8.7%
7 5
7.2%
, 4
5.8%
9 3
 
4.3%
Other values (2) 4
5.8%
Hangul
ValueCountFrequency (%)
월 1
33.3%
곡 1
33.3%
동 1
33.3%

Unnamed: 15
Text

MISSING 

Distinct23
Distinct (%)69.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T06:57:19.284738image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
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

Unique19 ?
Unique (%)57.6%

Sample

1st row비아동
2nd row3,518
3rd row7,478
4th row26
5th row6
ValueCountFrequency (%)
0 8
24.2%
26 3
 
9.1%
6 2
 
6.1%
28 2
 
6.1%
3,518 1
 
3.0%
7,478 1
 
3.0%
35 1
 
3.0%
3,522 1
 
3.0%
4 1
 
3.0%
2 1
 
3.0%
Other values (12) 12
36.4%
2024-02-10T06:57:20.355447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

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

Most occurring categories

ValueCountFrequency (%)
Decimal Number 59
88.1%
Other Punctuation 4
 
6.0%
Other Letter 3
 
4.5%
Dash Punctuation 1
 
1.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 12
20.3%
0 10
16.9%
6 7
11.9%
3 6
10.2%
8 5
8.5%
7 5
8.5%
5 5
8.5%
1 5
8.5%
4 4
 
6.8%
Other Letter
ValueCountFrequency (%)
비 1
33.3%
아 1
33.3%
동 1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
2 12
18.8%
0 10
15.6%
6 7
10.9%
3 6
9.4%
8 5
7.8%
7 5
7.8%
5 5
7.8%
1 5
7.8%
4 4
 
6.2%
, 4
 
6.2%
Hangul
ValueCountFrequency (%)
비 1
33.3%
아 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 (%)
2 12
18.8%
0 10
15.6%
6 7
10.9%
3 6
9.4%
8 5
7.8%
7 5
7.8%
5 5
7.8%
1 5
7.8%
4 4
 
6.2%
, 4
 
6.2%
Hangul
ValueCountFrequency (%)
비 1
33.3%
아 1
33.3%
동 1
33.3%

Unnamed: 16
Text

MISSING 

Distinct24
Distinct (%)72.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T06:57:20.861803image/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

Unique20 ?
Unique (%)60.6%

Sample

1st row첨단1동
2nd row10,723
3rd row27,156
4th row25
5th row14
ValueCountFrequency (%)
0 7
21.2%
10,723 2
 
6.1%
14 2
 
6.1%
59 2
 
6.1%
1 2
 
6.1%
102 1
 
3.0%
25 1
 
3.0%
203 1
 
3.0%
27,114 1
 
3.0%
42 1
 
3.0%
Other values (13) 13
39.4%
2024-02-10T06:57:21.815885image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 17
21.2%
0 12
15.0%
2 9
11.2%
5 7
8.8%
7 6
 
7.5%
4 6
 
7.5%
3 5
 
6.2%
8 5
 
6.2%
, 4
 
5.0%
9 2
 
2.5%
Other values (5) 7
8.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 71
88.8%
Other Punctuation 4
 
5.0%
Other Letter 3
 
3.8%
Dash Punctuation 2
 
2.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 17
23.9%
0 12
16.9%
2 9
12.7%
5 7
9.9%
7 6
 
8.5%
4 6
 
8.5%
3 5
 
7.0%
8 5
 
7.0%
9 2
 
2.8%
6 2
 
2.8%
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 77
96.2%
Hangul 3
 
3.8%

Most frequent character per script

Common
ValueCountFrequency (%)
1 17
22.1%
0 12
15.6%
2 9
11.7%
5 7
9.1%
7 6
 
7.8%
4 6
 
7.8%
3 5
 
6.5%
8 5
 
6.5%
, 4
 
5.2%
9 2
 
2.6%
Other values (2) 4
 
5.2%
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 17
22.1%
0 12
15.6%
2 9
11.7%
5 7
9.1%
7 6
 
7.8%
4 6
 
7.8%
3 5
 
6.5%
8 5
 
6.5%
, 4
 
5.2%
9 2
 
2.6%
Other values (2) 4
 
5.2%
Hangul
ValueCountFrequency (%)
첨 1
33.3%
단 1
33.3%
동 1
33.3%

Unnamed: 17
Text

MISSING 

Distinct27
Distinct (%)81.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T06:57:22.196108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length4
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

Unique26 ?
Unique (%)78.8%

Sample

1st row첨단2동
2nd row18,729
3rd row42,335
4th row63
5th row23
ValueCountFrequency (%)
0 7
21.2%
199 1
 
3.0%
252 1
 
3.0%
62 1
 
3.0%
42,295 1
 
3.0%
18,774 1
 
3.0%
1 1
 
3.0%
40 1
 
3.0%
45 1
 
3.0%
10 1
 
3.0%
Other values (17) 17
51.5%
2024-02-10T06:57:23.364033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 15
16.9%
0 13
14.6%
1 13
14.6%
4 8
9.0%
3 7
7.9%
5 6
 
6.7%
8 5
 
5.6%
7 5
 
5.6%
9 5
 
5.6%
, 4
 
4.5%
Other values (5) 8
9.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 80
89.9%
Other Punctuation 4
 
4.5%
Other Letter 3
 
3.4%
Dash Punctuation 2
 
2.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 15
18.8%
0 13
16.2%
1 13
16.2%
4 8
10.0%
3 7
8.8%
5 6
 
7.5%
8 5
 
6.2%
7 5
 
6.2%
9 5
 
6.2%
6 3
 
3.8%
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 86
96.6%
Hangul 3
 
3.4%

Most frequent character per script

Common
ValueCountFrequency (%)
2 15
17.4%
0 13
15.1%
1 13
15.1%
4 8
9.3%
3 7
8.1%
5 6
 
7.0%
8 5
 
5.8%
7 5
 
5.8%
9 5
 
5.8%
, 4
 
4.7%
Other values (2) 5
 
5.8%
Hangul
ValueCountFrequency (%)
첨 1
33.3%
단 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 (%)
2 15
17.4%
0 13
15.1%
1 13
15.1%
4 8
9.3%
3 7
8.1%
5 6
 
7.0%
8 5
 
5.8%
7 5
 
5.8%
9 5
 
5.8%
, 4
 
4.7%
Other values (2) 5
 
5.8%
Hangul
ValueCountFrequency (%)
첨 1
33.3%
단 1
33.3%
동 1
33.3%

Unnamed: 18
Text

MISSING 

Distinct26
Distinct (%)78.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T06:57:23.624831image/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 row신가동
2nd row7,409
3rd row19,317
4th row48
5th row5
ValueCountFrequency (%)
0 6
18.2%
37 2
 
6.1%
1 2
 
6.1%
3 2
 
6.1%
5 2
 
6.1%
56 1
 
3.0%
81 1
 
3.0%
19,311 1
 
3.0%
7,408 1
 
3.0%
6 1
 
3.0%
Other values (14) 14
42.4%
2024-02-10T06:57:24.502494image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 12
16.4%
5 10
13.7%
0 8
11.0%
3 8
11.0%
4 7
9.6%
7 6
8.2%
, 4
 
5.5%
6 4
 
5.5%
9 3
 
4.1%
8 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 (%)
1 12
19.0%
5 10
15.9%
0 8
12.7%
3 8
12.7%
4 7
11.1%
7 6
9.5%
6 4
 
6.3%
9 3
 
4.8%
8 3
 
4.8%
2 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 (%)
- 3
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
1 12
17.1%
5 10
14.3%
0 8
11.4%
3 8
11.4%
4 7
10.0%
7 6
8.6%
, 4
 
5.7%
6 4
 
5.7%
9 3
 
4.3%
8 3
 
4.3%
Other values (2) 5
7.1%
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 12
17.1%
5 10
14.3%
0 8
11.4%
3 8
11.4%
4 7
10.0%
7 6
8.6%
, 4
 
5.7%
6 4
 
5.7%
9 3
 
4.3%
8 3
 
4.3%
Other values (2) 5
7.1%
Hangul
ValueCountFrequency (%)
신 1
33.3%
가 1
33.3%
동 1
33.3%

Unnamed: 19
Text

MISSING 

Distinct27
Distinct (%)81.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T06:57:24.937083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length2
Mean length2.3636364
Min length1

Characters and Unicode

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

Unique

Unique25 ?
Unique (%)75.8%

Sample

1st row운남동
2nd row12,237
3rd row29,818
4th row21
5th row10
ValueCountFrequency (%)
0 6
 
18.2%
1 3
 
9.1%
185 1
 
3.0%
20 1
 
3.0%
29,803 1
 
3.0%
12,236 1
 
3.0%
15 1
 
3.0%
7 1
 
3.0%
54 1
 
3.0%
65 1
 
3.0%
Other values (16) 16
48.5%
2024-02-10T06:57:26.156912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 14
17.9%
0 11
14.1%
2 11
14.1%
8 7
9.0%
6 6
7.7%
5 5
 
6.4%
, 4
 
5.1%
3 4
 
5.1%
9 4
 
5.1%
4 4
 
5.1%
Other values (5) 8
10.3%

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 14
20.6%
0 11
16.2%
2 11
16.2%
8 7
10.3%
6 6
8.8%
5 5
 
7.4%
3 4
 
5.9%
9 4
 
5.9%
4 4
 
5.9%
7 2
 
2.9%
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 75
96.2%
Hangul 3
 
3.8%

Most frequent character per script

Common
ValueCountFrequency (%)
1 14
18.7%
0 11
14.7%
2 11
14.7%
8 7
9.3%
6 6
8.0%
5 5
 
6.7%
, 4
 
5.3%
3 4
 
5.3%
9 4
 
5.3%
4 4
 
5.3%
Other values (2) 5
 
6.7%
Hangul
ValueCountFrequency (%)
운 1
33.3%
남 1
33.3%
동 1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 14
18.7%
0 11
14.7%
2 11
14.7%
8 7
9.3%
6 6
8.0%
5 5
 
6.7%
, 4
 
5.3%
3 4
 
5.3%
9 4
 
5.3%
4 4
 
5.3%
Other values (2) 5
 
6.7%
Hangul
ValueCountFrequency (%)
운 1
33.3%
남 1
33.3%
동 1
33.3%

Unnamed: 20
Text

MISSING 

Distinct25
Distinct (%)75.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T06:57:26.557501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length3
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

Unique21 ?
Unique (%)63.6%

Sample

1st row수완동
2nd row28,259
3rd row75,677
4th row112
5th row18
ValueCountFrequency (%)
0 6
 
18.2%
2 2
 
6.1%
30 2
 
6.1%
135 2
 
6.1%
143 1
 
3.0%
18 1
 
3.0%
264 1
 
3.0%
114 1
 
3.0%
75,661 1
 
3.0%
28,289 1
 
3.0%
Other values (15) 15
45.5%
2024-02-10T06:57:27.492147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 18
20.0%
2 13
14.4%
0 8
8.9%
5 8
8.9%
6 7
 
7.8%
3 6
 
6.7%
4 6
 
6.7%
7 6
 
6.7%
9 5
 
5.6%
8 5
 
5.6%
Other values (5) 8
8.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 82
91.1%
Other Punctuation 4
 
4.4%
Other Letter 3
 
3.3%
Dash Punctuation 1
 
1.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 18
22.0%
2 13
15.9%
0 8
9.8%
5 8
9.8%
6 7
 
8.5%
3 6
 
7.3%
4 6
 
7.3%
7 6
 
7.3%
9 5
 
6.1%
8 5
 
6.1%
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 87
96.7%
Hangul 3
 
3.3%

Most frequent character per script

Common
ValueCountFrequency (%)
1 18
20.7%
2 13
14.9%
0 8
9.2%
5 8
9.2%
6 7
 
8.0%
3 6
 
6.9%
4 6
 
6.9%
7 6
 
6.9%
9 5
 
5.7%
8 5
 
5.7%
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 (%)
1 18
20.7%
2 13
14.9%
0 8
9.2%
5 8
9.2%
6 7
 
8.0%
3 6
 
6.9%
4 6
 
6.9%
7 6
 
6.9%
9 5
 
5.7%
8 5
 
5.7%
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
2024-02-10T06:57:27.888700image/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 row11,227
3rd row26,762
4th row42
5th row7
ValueCountFrequency (%)
0 6
 
18.2%
90 2
 
6.1%
11 2
 
6.1%
7 2
 
6.1%
118 1
 
3.0%
264 1
 
3.0%
26,708 1
 
3.0%
11,216 1
 
3.0%
4 1
 
3.0%
54 1
 
3.0%
Other values (15) 15
45.5%
2024-02-10T06:57:28.632263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 19
23.5%
0 11
13.6%
2 10
12.3%
6 9
11.1%
7 8
9.9%
4 6
 
7.4%
, 4
 
4.9%
9 3
 
3.7%
8 3
 
3.7%
5 2
 
2.5%
Other values (5) 6
 
7.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 72
88.9%
Other Punctuation 4
 
4.9%
Other Letter 3
 
3.7%
Dash Punctuation 2
 
2.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 19
26.4%
0 11
15.3%
2 10
13.9%
6 9
12.5%
7 8
11.1%
4 6
 
8.3%
9 3
 
4.2%
8 3
 
4.2%
5 2
 
2.8%
3 1
 
1.4%
Other Letter
ValueCountFrequency (%)
하 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 78
96.3%
Hangul 3
 
3.7%

Most frequent character per script

Common
ValueCountFrequency (%)
1 19
24.4%
0 11
14.1%
2 10
12.8%
6 9
11.5%
7 8
10.3%
4 6
 
7.7%
, 4
 
5.1%
9 3
 
3.8%
8 3
 
3.8%
5 2
 
2.6%
Other values (2) 3
 
3.8%
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 19
24.4%
0 11
14.1%
2 10
12.8%
6 9
11.5%
7 8
10.3%
4 6
 
7.7%
, 4
 
5.1%
9 3
 
3.8%
8 3
 
3.8%
5 2
 
2.6%
Other values (2) 3
 
3.8%
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
2024-02-10T06:57:29.063552image/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

Unique11 ?
Unique (%)33.3%

Sample

1st row임곡동
2nd row1,245
3rd row2,036
4th row13
5th row2
ValueCountFrequency (%)
0 9
27.3%
6 5
15.2%
2 3
 
9.1%
13 3
 
9.1%
3 2
 
6.1%
14 1
 
3.0%
1,245 1
 
3.0%
2,036 1
 
3.0%
10 1
 
3.0%
임곡동 1
 
3.0%
Other values (6) 6
18.2%
2024-02-10T06:57:30.048755image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 13
22.4%
1 8
13.8%
3 8
13.8%
2 7
12.1%
6 6
10.3%
, 4
 
6.9%
- 2
 
3.4%
4 2
 
3.4%
5 2
 
3.4%
9 2
 
3.4%
Other values (4) 4
 
6.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 49
84.5%
Other Punctuation 4
 
6.9%
Other Letter 3
 
5.2%
Dash Punctuation 2
 
3.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 13
26.5%
1 8
16.3%
3 8
16.3%
2 7
14.3%
6 6
12.2%
4 2
 
4.1%
5 2
 
4.1%
9 2
 
4.1%
8 1
 
2.0%
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 55
94.8%
Hangul 3
 
5.2%

Most frequent character per script

Common
ValueCountFrequency (%)
0 13
23.6%
1 8
14.5%
3 8
14.5%
2 7
12.7%
6 6
10.9%
, 4
 
7.3%
- 2
 
3.6%
4 2
 
3.6%
5 2
 
3.6%
9 2
 
3.6%
Hangul
ValueCountFrequency (%)
임 1
33.3%
곡 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 (%)
0 13
23.6%
1 8
14.5%
3 8
14.5%
2 7
12.7%
6 6
10.9%
, 4
 
7.3%
- 2
 
3.6%
4 2
 
3.6%
5 2
 
3.6%
9 2
 
3.6%
Hangul
ValueCountFrequency (%)
임 1
33.3%
곡 1
33.3%
동 1
33.3%

Unnamed: 23
Categorical

Distinct16
Distinct (%)45.7%
Missing0
Missing (%)0.0%
Memory size412.0 B
0
9 
2
7 
4
5 
<NA>
2 
동곡동
 
1
Other values (11)
11 

Length

Max length5
Median length1
Mean length1.6857143
Min length1

Unique

Unique12 ?
Unique (%)34.3%

Sample

1st row<NA>
2nd row<NA>
3rd row동곡동
4th row993
5th row1,747

Common Values

ValueCountFrequency (%)
0 9
25.7%
2 7
20.0%
4 5
14.3%
<NA> 2
 
5.7%
동곡동 1
 
2.9%
993 1
 
2.9%
1,747 1
 
2.9%
11 1
 
2.9%
7 1
 
2.9%
5 1
 
2.9%
Other values (6) 6
17.1%

Length

2024-02-10T06:57:30.543567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
0 9
25.7%
2 7
20.0%
4 6
17.1%
na 2
 
5.7%
1 2
 
5.7%
동곡동 1
 
2.9%
993 1
 
2.9%
1,747 1
 
2.9%
11 1
 
2.9%
7 1
 
2.9%
Other values (4) 4
11.4%

Unnamed: 24
Text

MISSING 

Distinct20
Distinct (%)60.6%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T06:57:30.902426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length2
Mean length1.969697
Min length1

Characters and Unicode

Total characters65
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

Unique14 ?
Unique (%)42.4%

Sample

1st row평동
2nd row2,988
3rd row4,903
4th row11
5th row3
ValueCountFrequency (%)
0 8
24.2%
3 3
 
9.1%
21 2
 
6.1%
18 2
 
6.1%
17 2
 
6.1%
11 2
 
6.1%
50 1
 
3.0%
56 1
 
3.0%
38 1
 
3.0%
4,903 1
 
3.0%
Other values (10) 10
30.3%
2024-02-10T06:57:31.943401image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 13
20.0%
0 11
16.9%
3 7
10.8%
8 6
9.2%
2 5
 
7.7%
4 4
 
6.2%
, 4
 
6.2%
9 4
 
6.2%
7 3
 
4.6%
5 3
 
4.6%
Other values (4) 5
 
7.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 58
89.2%
Other Punctuation 4
 
6.2%
Other Letter 2
 
3.1%
Dash Punctuation 1
 
1.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 13
22.4%
0 11
19.0%
3 7
12.1%
8 6
10.3%
2 5
 
8.6%
4 4
 
6.9%
9 4
 
6.9%
7 3
 
5.2%
5 3
 
5.2%
6 2
 
3.4%
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 63
96.9%
Hangul 2
 
3.1%

Most frequent character per script

Common
ValueCountFrequency (%)
1 13
20.6%
0 11
17.5%
3 7
11.1%
8 6
9.5%
2 5
 
7.9%
4 4
 
6.3%
, 4
 
6.3%
9 4
 
6.3%
7 3
 
4.8%
5 3
 
4.8%
Other values (2) 3
 
4.8%
Hangul
ValueCountFrequency (%)
평 1
50.0%
동 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 63
96.9%
Hangul 2
 
3.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 13
20.6%
0 11
17.5%
3 7
11.1%
8 6
9.5%
2 5
 
7.9%
4 4
 
6.3%
, 4
 
6.3%
9 4
 
6.3%
7 3
 
4.8%
5 3
 
4.8%
Other values (2) 3
 
4.8%
Hangul
ValueCountFrequency (%)
평 1
50.0%
동 1
50.0%

Unnamed: 25
Text

MISSING 

Distinct17
Distinct (%)51.5%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T06:57:32.804537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length1
Mean length1.6363636
Min length1

Characters and Unicode

Total characters54
Distinct characters14
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique11 ?
Unique (%)33.3%

Sample

1st row삼도동
2nd row1,326
3rd row2,153
4th row6
5th row0
ValueCountFrequency (%)
0 10
30.3%
6 4
 
12.1%
7 2
 
6.1%
4 2
 
6.1%
1 2
 
6.1%
8 2
 
6.1%
삼도동 1
 
3.0%
14 1
 
3.0%
21 1
 
3.0%
2,153 1
 
3.0%
Other values (7) 7
21.2%
2024-02-10T06:57:34.447875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 11
20.4%
1 9
16.7%
6 6
11.1%
3 6
11.1%
2 5
9.3%
, 4
 
7.4%
4 3
 
5.6%
7 2
 
3.7%
8 2
 
3.7%
5 2
 
3.7%
Other values (4) 4
 
7.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 47
87.0%
Other Punctuation 4
 
7.4%
Other Letter 3
 
5.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 11
23.4%
1 9
19.1%
6 6
12.8%
3 6
12.8%
2 5
10.6%
4 3
 
6.4%
7 2
 
4.3%
8 2
 
4.3%
5 2
 
4.3%
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%

Most occurring scripts

ValueCountFrequency (%)
Common 51
94.4%
Hangul 3
 
5.6%

Most frequent character per script

Common
ValueCountFrequency (%)
0 11
21.6%
1 9
17.6%
6 6
11.8%
3 6
11.8%
2 5
9.8%
, 4
 
7.8%
4 3
 
5.9%
7 2
 
3.9%
8 2
 
3.9%
5 2
 
3.9%
Hangul
ValueCountFrequency (%)
삼 1
33.3%
도 1
33.3%
동 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 51
94.4%
Hangul 3
 
5.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 11
21.6%
1 9
17.6%
6 6
11.8%
3 6
11.8%
2 5
9.8%
, 4
 
7.8%
4 3
 
5.9%
7 2
 
3.9%
8 2
 
3.9%
5 2
 
3.9%
Hangul
ValueCountFrequency (%)
삼 1
33.3%
도 1
33.3%
동 1
33.3%

Unnamed: 26
Categorical

Distinct17
Distinct (%)48.6%
Missing0
Missing (%)0.0%
Memory size412.0 B
0
11 
4
4 
3
4 
<NA>
2 
5
2 
Other values (12)
12 

Length

Max length5
Median length1
Mean length1.8
Min length1

Unique

Unique12 ?
Unique (%)34.3%

Sample

1st row<NA>
2nd row<NA>
3rd row본량동
4th row1,176
5th row1,928

Common Values

ValueCountFrequency (%)
0 11
31.4%
4 4
 
11.4%
3 4
 
11.4%
<NA> 2
 
5.7%
5 2
 
5.7%
본량동 1
 
2.9%
1,176 1
 
2.9%
1,928 1
 
2.9%
21 1
 
2.9%
13 1
 
2.9%
Other values (7) 7
20.0%

Length

2024-02-10T06:57:35.321669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
0 11
31.4%
3 4
 
11.4%
4 4
 
11.4%
na 2
 
5.7%
5 2
 
5.7%
12 1
 
2.9%
1,180 1
 
2.9%
6 1
 
2.9%
7 1
 
2.9%
8 1
 
2.9%
Other values (7) 7
20.0%

Unnamed: 27
Text

MISSING 

Distinct21
Distinct (%)63.6%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T06:57:35.983497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length3
Mean length2.4848485
Min length1

Characters and Unicode

Total characters82
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

Unique16 ?
Unique (%)48.5%

Sample

1st row신창동
2nd row13,856
3rd row34,182
4th row68
5th row11
ValueCountFrequency (%)
0 8
24.2%
68 3
 
9.1%
11 2
 
6.1%
52 2
 
6.1%
102 2
 
6.1%
221 1
 
3.0%
278 1
 
3.0%
150 1
 
3.0%
128 1
 
3.0%
34,182 1
 
3.0%
Other values (11) 11
33.3%
2024-02-10T06:57:36.954061image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 16
19.5%
0 13
15.9%
8 10
12.2%
2 10
12.2%
6 7
8.5%
5 6
 
7.3%
3 5
 
6.1%
, 4
 
4.9%
4 4
 
4.9%
7 3
 
3.7%
Other values (4) 4
 
4.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 75
91.5%
Other Punctuation 4
 
4.9%
Other Letter 3
 
3.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 16
21.3%
0 13
17.3%
8 10
13.3%
2 10
13.3%
6 7
9.3%
5 6
 
8.0%
3 5
 
6.7%
4 4
 
5.3%
7 3
 
4.0%
9 1
 
1.3%
Other Letter
ValueCountFrequency (%)
신 1
33.3%
창 1
33.3%
동 1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
1 16
20.3%
0 13
16.5%
8 10
12.7%
2 10
12.7%
6 7
8.9%
5 6
 
7.6%
3 5
 
6.3%
, 4
 
5.1%
4 4
 
5.1%
7 3
 
3.8%
Hangul
ValueCountFrequency (%)
신 1
33.3%
창 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 16
20.3%
0 13
16.5%
8 10
12.7%
2 10
12.7%
6 7
8.9%
5 6
 
7.6%
3 5
 
6.3%
, 4
 
5.1%
4 4
 
5.1%
7 3
 
3.8%
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>2023.05.17<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
1<NA>작성기준 :<NA>2023.04 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>171,0174,8043,4356,6402,01414,32914,985<NA>4,7676,3573,51810,72318,7297,40912,23728,25911,2271,2459932,9881,3261,17613,856
4<NA>전월말인구수<NA><NA><NA>399,14910,5296,31914,7724,40733,27229,408<NA>10,20814,7427,47827,15642,33519,31729,81875,67726,7622,0361,7474,9032,1531,92834,182
5<NA>전월말거주불명자수<NA><NA><NA>790445821213491<NA>4635262563482111242132116368
6<NA>전월말재외국민등록자수<NA><NA><NA>145183377<NA>76614235101872430011
7<NA>증 가 요 인전 입계<NA>2,997776411426221392<NA>707846157400125162465207134562121278
8<NA><NA><NA>남자<NA>1,65048295712130199<NA>415325842227280254117102381413150
9<NA><NA><NA>여자<NA>1,3472935571491193<NA>29252173178538221190321878128
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>1100000<NA>000000000000000
26<NA><NA>국외<NA><NA>0000000<NA>000000000000000
27<NA><NA>기타<NA><NA>0000000<NA>000000000000000
28<NA>세대수증감<NA><NA><NA>18011-151-5689<NA>-16-74045-1-130-11-6-4-59452
29<NA>인구수증감<NA><NA><NA>-208-3-13-38-12-4495<NA>-18-44-26-42-40-6-15-16-54-6-9410465
30<NA>거주불명자수증감<NA><NA><NA>14080-242<NA>-140-1-1-3-1240-10000
31<NA>금월말세대수<NA><NA><NA>171,1974,8153,4206,6412,00914,33515,074<NA>4,7516,3503,52210,72318,7747,40812,23628,28911,2161,2399892,9831,3351,18013,908
32<NA>금월말인구수<NA><NA><NA>398,94110,5266,30614,7344,39533,22829,503<NA>10,19014,6987,45227,11442,29519,31129,80375,66126,7082,0301,7384,9072,1631,93234,247
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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>기타<NA><NA>0000000<NA>0000000000000002