Overview

Dataset statistics

Number of variables35
Number of observations35
Missing cells223
Missing cells (%)18.2%
Duplicate rows1
Duplicate rows (%)2.9%
Total size in memory9.7 KiB
Average record size in memory284.8 B

Variable types

Unsupported1
Text33
DateTime1

Dataset

Description2022-12-16
Author주민등록인구통계
URLhttps://bigdata.gwangju.go.kr/usr/dataSet/getDataDetailView.rd?dataSetUncd=DS000201927

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: 23 has 2 (5.7%) missing valuesMissing
Unnamed: 24 has 2 (5.7%) missing valuesMissing
Unnamed: 25 has 2 (5.7%) missing valuesMissing
Unnamed: 26 has 2 (5.7%) missing valuesMissing
Unnamed: 27 has 2 (5.7%) missing valuesMissing
Unnamed: 28 has 2 (5.7%) missing valuesMissing
Unnamed: 29 has 2 (5.7%) missing valuesMissing
Unnamed: 30 has 2 (5.7%) missing valuesMissing
Unnamed: 31 has 2 (5.7%) missing valuesMissing
Unnamed: 32 has 2 (5.7%) missing valuesMissing
Unnamed: 33 has 2 (5.7%) missing valuesMissing
Unnamed: 34 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 09:37:23.679368
Analysis finished2024-02-10 09:37:25.624977
Duration1.95 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
Distinct16
Distinct (%)100.0%
Missing19
Missing (%)54.3%
Memory size412.0 B
2024-02-10T09:37:25.958879image/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 (%)
2
 
7.7%
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%
1
 
3.8%
Other values (13) 13
50.0%
2024-02-10T09:37:27.068510image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
12
 
9.5%
11
 
8.7%
8
 
6.3%
8
 
6.3%
5
 
4.0%
5
 
4.0%
4
 
3.2%
4
 
3.2%
4
 
3.2%
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 (%)
11
 
10.6%
8
 
7.7%
8
 
7.7%
5
 
4.8%
5
 
4.8%
4
 
3.8%
4
 
3.8%
4
 
3.8%
4
 
3.8%
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 (%)
11
 
10.6%
8
 
7.7%
8
 
7.7%
5
 
4.8%
5
 
4.8%
4
 
3.8%
4
 
3.8%
4
 
3.8%
4
 
3.8%
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 (%)
11
 
10.6%
8
 
7.7%
8
 
7.7%
5
 
4.8%
5
 
4.8%
4
 
3.8%
4
 
3.8%
4
 
3.8%
4
 
3.8%
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
2024-02-10T09:37:27.553662image/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%
2
15.4%
1
7.7%
복귀 1
7.7%
출생 1
7.7%
등록 1
7.7%
1
7.7%
사망 1
7.7%
말소 1
7.7%
2024-02-10T09:37:28.408001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4
15.4%
2
 
7.7%
2
 
7.7%
2
 
7.7%
2
 
7.7%
2
 
7.7%
2
 
7.7%
1
 
3.8%
1
 
3.8%
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 (%)
2
 
9.1%
2
 
9.1%
2
 
9.1%
2
 
9.1%
2
 
9.1%
2
 
9.1%
1
 
4.5%
1
 
4.5%
1
 
4.5%
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 (%)
2
 
9.1%
2
 
9.1%
2
 
9.1%
2
 
9.1%
2
 
9.1%
2
 
9.1%
1
 
4.5%
1
 
4.5%
1
 
4.5%
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 (%)
2
 
9.1%
2
 
9.1%
2
 
9.1%
2
 
9.1%
2
 
9.1%
2
 
9.1%
1
 
4.5%
1
 
4.5%
1
 
4.5%
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
2024-02-10T09:37:28.832038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length9
Mean length3.4166667
Min length1

Characters and Unicode

Total characters41
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 북구
2nd row2022.11 현재
3rd row
4th row남자
5th row여자
ValueCountFrequency (%)
2
14.3%
남자 2
14.3%
여자 2
14.3%
시도내 2
14.3%
시도간 2
14.3%
광주광역시 1
7.1%
북구 1
7.1%
2022.11 1
7.1%
현재 1
7.1%
2024-02-10T09:37:29.819736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5
12.2%
4
 
9.8%
4
 
9.8%
3
 
7.3%
2 3
 
7.3%
2
 
4.9%
2
 
4.9%
2
 
4.9%
2
 
4.9%
2
 
4.9%
Other values (10) 12
29.3%

Most occurring categories

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

Most frequent character per category

Other Letter
ValueCountFrequency (%)
5
16.1%
4
12.9%
4
12.9%
2
 
6.5%
2
 
6.5%
2
 
6.5%
2
 
6.5%
2
 
6.5%
2
 
6.5%
1
 
3.2%
Other values (5) 5
16.1%
Decimal Number
ValueCountFrequency (%)
2 3
50.0%
1 2
33.3%
0 1
 
16.7%
Space Separator
ValueCountFrequency (%)
3
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%

Most occurring scripts

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

Most frequent character per script

Hangul
ValueCountFrequency (%)
5
16.1%
4
12.9%
4
12.9%
2
 
6.5%
2
 
6.5%
2
 
6.5%
2
 
6.5%
2
 
6.5%
2
 
6.5%
1
 
3.2%
Other values (5) 5
16.1%
Common
ValueCountFrequency (%)
3
30.0%
2 3
30.0%
1 2
20.0%
0 1
 
10.0%
. 1
 
10.0%

Most occurring blocks

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

Most frequent character per block

Hangul
ValueCountFrequency (%)
5
16.1%
4
12.9%
4
12.9%
2
 
6.5%
2
 
6.5%
2
 
6.5%
2
 
6.5%
2
 
6.5%
2
 
6.5%
1
 
3.2%
Other values (5) 5
16.1%
ASCII
ValueCountFrequency (%)
3
30.0%
2 3
30.0%
1 2
20.0%
0 1
 
10.0%
. 1
 
10.0%

Unnamed: 4
Text

MISSING 

Distinct2
Distinct (%)50.0%
Missing31
Missing (%)88.6%
Memory size412.0 B
2024-02-10T09:37:30.285712image/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%
2024-02-10T09:37:31.093149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4
25.0%
4
25.0%
4
25.0%
2
12.5%
2
12.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 16
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
4
25.0%
4
25.0%
4
25.0%
2
12.5%
2
12.5%

Most occurring scripts

ValueCountFrequency (%)
Hangul 16
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
4
25.0%
4
25.0%
4
25.0%
2
12.5%
2
12.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 16
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
4
25.0%
4
25.0%
4
25.0%
2
12.5%
2
12.5%

Unnamed: 5
Text

MISSING 

Distinct29
Distinct (%)87.9%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:37:31.713538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length3.7575758
Min length1

Characters and Unicode

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

Unique

Unique27 ?
Unique (%)81.8%

Sample

1st row합 계
2nd row198,023
3rd row424,720
4th row883
5th row224
ValueCountFrequency (%)
0 4
 
11.8%
2,254 2
 
5.9%
4,895 1
 
2.9%
876 1
 
2.9%
425,001 1
 
2.9%
198,058 1
 
2.9%
7 1
 
2.9%
281 1
 
2.9%
35 1
 
2.9%
2 1
 
2.9%
Other values (20) 20
58.8%
2024-02-10T09:37:32.581920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 25
20.2%
, 16
12.9%
1 14
11.3%
4 13
10.5%
0 11
8.9%
5 11
8.9%
8 10
 
8.1%
3 7
 
5.6%
9 5
 
4.0%
7 4
 
3.2%
Other values (5) 8
 
6.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 103
83.1%
Other Punctuation 16
 
12.9%
Space Separator 2
 
1.6%
Other Letter 2
 
1.6%
Dash Punctuation 1
 
0.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 25
24.3%
1 14
13.6%
4 13
12.6%
0 11
10.7%
5 11
10.7%
8 10
 
9.7%
3 7
 
6.8%
9 5
 
4.9%
7 4
 
3.9%
6 3
 
2.9%
Other Letter
ValueCountFrequency (%)
1
50.0%
1
50.0%
Other Punctuation
ValueCountFrequency (%)
, 16
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
2 25
20.5%
, 16
13.1%
1 14
11.5%
4 13
10.7%
0 11
9.0%
5 11
9.0%
8 10
 
8.2%
3 7
 
5.7%
9 5
 
4.1%
7 4
 
3.3%
Other values (3) 6
 
4.9%
Hangul
ValueCountFrequency (%)
1
50.0%
1
50.0%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 25
20.5%
, 16
13.1%
1 14
11.5%
4 13
10.7%
0 11
9.0%
5 11
9.0%
8 10
 
8.2%
3 7
 
5.7%
9 5
 
4.1%
7 4
 
3.3%
Other values (3) 6
 
4.9%
Hangul
ValueCountFrequency (%)
1
50.0%
1
50.0%

Unnamed: 6
Text

MISSING 

Distinct24
Distinct (%)72.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:37:33.037048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length2.1515152
Min length1

Characters and Unicode

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

Unique

Unique22 ?
Unique (%)66.7%

Sample

1st row중흥1동
2nd row2,947
3rd row4,623
4th row42
5th row0
ValueCountFrequency (%)
0 9
27.3%
31 2
 
6.1%
42 2
 
6.1%
3 1
 
3.0%
52 1
 
3.0%
4,593 1
 
3.0%
2,916 1
 
3.0%
1 1
 
3.0%
30 1
 
3.0%
4 1
 
3.0%
Other values (13) 13
39.4%
2024-02-10T09:37:34.078864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

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

Most occurring categories

ValueCountFrequency (%)
Decimal Number 61
85.9%
Other Punctuation 4
 
5.6%
Dash Punctuation 3
 
4.2%
Other Letter 3
 
4.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 10
16.4%
4 10
16.4%
2 10
16.4%
3 8
13.1%
1 8
13.1%
6 5
8.2%
9 4
 
6.6%
5 4
 
6.6%
7 1
 
1.6%
8 1
 
1.6%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
0 10
14.7%
4 10
14.7%
2 10
14.7%
3 8
11.8%
1 8
11.8%
6 5
7.4%
9 4
 
5.9%
, 4
 
5.9%
5 4
 
5.9%
- 3
 
4.4%
Other values (2) 2
 
2.9%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 10
14.7%
4 10
14.7%
2 10
14.7%
3 8
11.8%
1 8
11.8%
6 5
7.4%
9 4
 
5.9%
, 4
 
5.9%
5 4
 
5.9%
- 3
 
4.4%
Other values (2) 2
 
2.9%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 7
Text

MISSING 

Distinct25
Distinct (%)75.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:37:34.497546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
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

Unique22 ?
Unique (%)66.7%

Sample

1st row중흥2동
2nd row4,414
3rd row8,478
4th row24
5th row6
ValueCountFrequency (%)
0 7
21.2%
39 2
 
6.1%
6 2
 
6.1%
5 1
 
3.0%
88 1
 
3.0%
8,425 1
 
3.0%
4,382 1
 
3.0%
2 1
 
3.0%
53 1
 
3.0%
32 1
 
3.0%
Other values (15) 15
45.5%
2024-02-10T09:37:35.680321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 11
15.3%
4 11
15.3%
8 9
12.5%
0 7
9.7%
6 5
6.9%
3 5
6.9%
5 5
6.9%
1 4
 
5.6%
, 4
 
5.6%
9 3
 
4.2%
Other values (5) 8
11.1%

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 (%)
2 11
17.5%
4 11
17.5%
8 9
14.3%
0 7
11.1%
6 5
7.9%
3 5
7.9%
5 5
7.9%
1 4
 
6.3%
9 3
 
4.8%
7 3
 
4.8%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
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 (%)
2 11
15.9%
4 11
15.9%
8 9
13.0%
0 7
10.1%
6 5
7.2%
3 5
7.2%
5 5
7.2%
1 4
 
5.8%
, 4
 
5.8%
9 3
 
4.3%
Other values (2) 5
7.2%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 11
15.9%
4 11
15.9%
8 9
13.0%
0 7
10.1%
6 5
7.2%
3 5
7.2%
5 5
7.2%
1 4
 
5.8%
, 4
 
5.8%
9 3
 
4.3%
Other values (2) 5
7.2%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 8
Text

MISSING 

Distinct25
Distinct (%)75.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:37:36.203932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length2.2121212
Min length1

Characters and Unicode

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

Unique

Unique21 ?
Unique (%)63.6%

Sample

1st row중흥3동
2nd row3,634
3rd row6,550
4th row46
5th row3
ValueCountFrequency (%)
0 6
 
18.2%
35 2
 
6.1%
32 2
 
6.1%
3 2
 
6.1%
81 1
 
3.0%
88 1
 
3.0%
40 1
 
3.0%
6,515 1
 
3.0%
3,599 1
 
3.0%
6 1
 
3.0%
Other values (15) 15
45.5%
2024-02-10T09:37:37.447592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 13
17.8%
5 9
12.3%
0 8
11.0%
6 7
9.6%
1 6
8.2%
2 5
 
6.8%
9 5
 
6.8%
4 5
 
6.8%
, 4
 
5.5%
- 3
 
4.1%
Other values (5) 8
11.0%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 13
20.6%
5 9
14.3%
0 8
12.7%
6 7
11.1%
1 6
9.5%
2 5
 
7.9%
9 5
 
7.9%
4 5
 
7.9%
8 3
 
4.8%
7 2
 
3.2%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
3 13
18.6%
5 9
12.9%
0 8
11.4%
6 7
10.0%
1 6
8.6%
2 5
 
7.1%
9 5
 
7.1%
4 5
 
7.1%
, 4
 
5.7%
- 3
 
4.3%
Other values (2) 5
 
7.1%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 13
18.6%
5 9
12.9%
0 8
11.4%
6 7
10.0%
1 6
8.6%
2 5
 
7.1%
9 5
 
7.1%
4 5
 
7.1%
, 4
 
5.7%
- 3
 
4.3%
Other values (2) 5
 
7.1%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 9
Text

MISSING 

Distinct25
Distinct (%)75.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:37:37.813762image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
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

Unique23 ?
Unique (%)69.7%

Sample

1st row중앙동
2nd row2,337
3rd row3,975
4th row27
5th row5
ValueCountFrequency (%)
0 8
24.2%
26 2
 
6.1%
3 1
 
3.0%
93 1
 
3.0%
3,958 1
 
3.0%
2,309 1
 
3.0%
1 1
 
3.0%
17 1
 
3.0%
28 1
 
3.0%
23 1
 
3.0%
Other values (15) 15
45.5%
2024-02-10T09:37:38.644167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 12
17.1%
0 9
12.9%
2 7
10.0%
7 7
10.0%
6 6
8.6%
4 6
8.6%
, 4
 
5.7%
9 4
 
5.7%
1 4
 
5.7%
5 3
 
4.3%
Other values (5) 8
11.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 60
85.7%
Other Punctuation 4
 
5.7%
Dash Punctuation 3
 
4.3%
Other Letter 3
 
4.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 12
20.0%
0 9
15.0%
2 7
11.7%
7 7
11.7%
6 6
10.0%
4 6
10.0%
9 4
 
6.7%
1 4
 
6.7%
5 3
 
5.0%
8 2
 
3.3%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
3 12
17.9%
0 9
13.4%
2 7
10.4%
7 7
10.4%
6 6
9.0%
4 6
9.0%
, 4
 
6.0%
9 4
 
6.0%
1 4
 
6.0%
5 3
 
4.5%
Other values (2) 5
7.5%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 12
17.9%
0 9
13.4%
2 7
10.4%
7 7
10.4%
6 6
9.0%
4 6
9.0%
, 4
 
6.0%
9 4
 
6.0%
1 4
 
6.0%
5 3
 
4.5%
Other values (2) 5
7.5%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 10
Text

MISSING 

Distinct25
Distinct (%)73.5%
Missing1
Missing (%)2.9%
Memory size412.0 B
2024-02-10T09:37:39.062366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.2352941
Min length1

Characters and Unicode

Total characters76
Distinct characters20
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

Unique21 ?
Unique (%)61.8%

Sample

1st row출력일자 :
2nd row임동
3rd row4,634
4th row9,137
5th row26
ValueCountFrequency (%)
0 7
20.0%
60 2
 
5.7%
26 2
 
5.7%
5 2
 
5.7%
1
 
2.9%
1 1
 
2.9%
4,623 1
 
2.9%
22 1
 
2.9%
11 1
 
2.9%
4 1
 
2.9%
Other values (16) 16
45.7%
2024-02-10T09:37:40.063597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 10
13.2%
3 10
13.2%
1 10
13.2%
5 9
11.8%
6 6
7.9%
4 6
7.9%
2 5
6.6%
, 4
 
5.3%
9 3
 
3.9%
7 2
 
2.6%
Other values (10) 11
14.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 62
81.6%
Other Letter 6
 
7.9%
Other Punctuation 5
 
6.6%
Dash Punctuation 2
 
2.6%
Space Separator 1
 
1.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 10
16.1%
3 10
16.1%
1 10
16.1%
5 9
14.5%
6 6
9.7%
4 6
9.7%
2 5
8.1%
9 3
 
4.8%
7 2
 
3.2%
8 1
 
1.6%
Other Letter
ValueCountFrequency (%)
1
16.7%
1
16.7%
1
16.7%
1
16.7%
1
16.7%
1
16.7%
Other Punctuation
ValueCountFrequency (%)
, 4
80.0%
: 1
 
20.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 70
92.1%
Hangul 6
 
7.9%

Most frequent character per script

Common
ValueCountFrequency (%)
0 10
14.3%
3 10
14.3%
1 10
14.3%
5 9
12.9%
6 6
8.6%
4 6
8.6%
2 5
7.1%
, 4
 
5.7%
9 3
 
4.3%
7 2
 
2.9%
Other values (4) 5
7.1%
Hangul
ValueCountFrequency (%)
1
16.7%
1
16.7%
1
16.7%
1
16.7%
1
16.7%
1
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 70
92.1%
Hangul 6
 
7.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 10
14.3%
3 10
14.3%
1 10
14.3%
5 9
12.9%
6 6
8.6%
4 6
8.6%
2 5
7.1%
, 4
 
5.7%
9 3
 
4.3%
7 2
 
2.9%
Other values (4) 5
7.1%
Hangul
ValueCountFrequency (%)
1
16.7%
1
16.7%
1
16.7%
1
16.7%
1
16.7%
1
16.7%

Unnamed: 11
Text

MISSING 

Distinct26
Distinct (%)78.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:37:40.475489image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.2424242
Min length1

Characters and Unicode

Total characters74
Distinct characters15
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique24 ?
Unique (%)72.7%

Sample

1st row신안동
2nd row7,469
3rd row12,598
4th row63
5th row1
ValueCountFrequency (%)
0 7
21.2%
1 3
 
9.1%
96 1
 
3.0%
104 1
 
3.0%
12,565 1
 
3.0%
7,475 1
 
3.0%
33 1
 
3.0%
6 1
 
3.0%
14 1
 
3.0%
61 1
 
3.0%
Other values (15) 15
45.5%
2024-02-10T09:37:41.879218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6 11
14.9%
0 10
13.5%
1 9
12.2%
5 7
9.5%
2 6
8.1%
7 6
8.1%
9 5
6.8%
, 4
 
5.4%
4 4
 
5.4%
3 4
 
5.4%
Other values (5) 8
10.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 65
87.8%
Other Punctuation 4
 
5.4%
Other Letter 3
 
4.1%
Dash Punctuation 2
 
2.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
6 11
16.9%
0 10
15.4%
1 9
13.8%
5 7
10.8%
2 6
9.2%
7 6
9.2%
9 5
7.7%
4 4
 
6.2%
3 4
 
6.2%
8 3
 
4.6%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 71
95.9%
Hangul 3
 
4.1%

Most frequent character per script

Common
ValueCountFrequency (%)
6 11
15.5%
0 10
14.1%
1 9
12.7%
5 7
9.9%
2 6
8.5%
7 6
8.5%
9 5
7.0%
, 4
 
5.6%
4 4
 
5.6%
3 4
 
5.6%
Other values (2) 5
7.0%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 71
95.9%
Hangul 3
 
4.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6 11
15.5%
0 10
14.1%
1 9
12.7%
5 7
9.9%
2 6
8.5%
7 6
8.5%
9 5
7.0%
, 4
 
5.6%
4 4
 
5.6%
3 4
 
5.6%
Other values (2) 5
7.0%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 12
Date

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing34
Missing (%)97.1%
Memory size412.0 B
Minimum2022-12-12 00:00:00
Maximum2022-12-12 00:00:00
2024-02-10T09:37:42.272958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-10T09:37:42.544620image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Unnamed: 13
Text

MISSING 

Distinct26
Distinct (%)78.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:37:43.002426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length3
Mean length2.6060606
Min length1

Characters and Unicode

Total characters86
Distinct characters15
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique24 ?
Unique (%)72.7%

Sample

1st row용봉동
2nd row17,831
3rd row37,736
4th row81
5th row20
ValueCountFrequency (%)
0 7
21.2%
20 2
 
6.1%
239 1
 
3.0%
37,650 1
 
3.0%
17,836 1
 
3.0%
2 1
 
3.0%
86 1
 
3.0%
5 1
 
3.0%
21 1
 
3.0%
155 1
 
3.0%
Other values (16) 16
48.5%
2024-02-10T09:37:43.979653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 14
16.3%
0 12
14.0%
3 11
12.8%
8 8
9.3%
2 7
8.1%
5 7
8.1%
7 6
7.0%
6 6
7.0%
9 5
 
5.8%
, 4
 
4.7%
Other values (5) 6
7.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 78
90.7%
Other Punctuation 4
 
4.7%
Other Letter 3
 
3.5%
Dash Punctuation 1
 
1.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 14
17.9%
0 12
15.4%
3 11
14.1%
8 8
10.3%
2 7
9.0%
5 7
9.0%
7 6
7.7%
6 6
7.7%
9 5
 
6.4%
4 2
 
2.6%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
1 14
16.9%
0 12
14.5%
3 11
13.3%
8 8
9.6%
2 7
8.4%
5 7
8.4%
7 6
7.2%
6 6
7.2%
9 5
 
6.0%
, 4
 
4.8%
Other values (2) 3
 
3.6%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 14
16.9%
0 12
14.5%
3 11
13.3%
8 8
9.6%
2 7
8.4%
5 7
8.4%
7 6
7.2%
6 6
7.2%
9 5
 
6.0%
, 4
 
4.8%
Other values (2) 3
 
3.6%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 14
Text

MISSING 

Distinct21
Distinct (%)63.6%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:37:44.408966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.3030303
Min length1

Characters and Unicode

Total characters76
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

Unique16 ?
Unique (%)48.5%

Sample

1st row운암1동
2nd row7,429
3rd row18,975
4th row18
5th row18
ValueCountFrequency (%)
0 7
21.2%
18 4
 
12.1%
59 2
 
6.1%
50 2
 
6.1%
49 2
 
6.1%
1 1
 
3.0%
108 1
 
3.0%
18,975 1
 
3.0%
28 1
 
3.0%
30 1
 
3.0%
Other values (11) 11
33.3%
2024-02-10T09:37:45.335843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
8 13
17.1%
0 12
15.8%
1 12
15.8%
5 7
9.2%
9 7
9.2%
4 6
7.9%
7 6
7.9%
, 4
 
5.3%
2 3
 
3.9%
- 2
 
2.6%
Other values (4) 4
 
5.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 67
88.2%
Other Punctuation 4
 
5.3%
Other Letter 3
 
3.9%
Dash Punctuation 2
 
2.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
8 13
19.4%
0 12
17.9%
1 12
17.9%
5 7
10.4%
9 7
10.4%
4 6
9.0%
7 6
9.0%
2 3
 
4.5%
3 1
 
1.5%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
8 13
17.8%
0 12
16.4%
1 12
16.4%
5 7
9.6%
9 7
9.6%
4 6
8.2%
7 6
8.2%
, 4
 
5.5%
2 3
 
4.1%
- 2
 
2.7%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
8 13
17.8%
0 12
16.4%
1 12
16.4%
5 7
9.6%
9 7
9.6%
4 6
8.2%
7 6
8.2%
, 4
 
5.5%
2 3
 
4.1%
- 2
 
2.7%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 15
Text

MISSING 

Distinct25
Distinct (%)75.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:37:45.960674image/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

Unique22 ?
Unique (%)66.7%

Sample

1st row운암2동
2nd row6,038
3rd row11,600
4th row52
5th row9
ValueCountFrequency (%)
0 7
21.2%
92 2
 
6.1%
1 2
 
6.1%
9 2
 
6.1%
64 1
 
3.0%
49 1
 
3.0%
11,541 1
 
3.0%
6,007 1
 
3.0%
59 1
 
3.0%
31 1
 
3.0%
Other values (14) 14
42.4%
2024-02-10T09:37:46.791132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 13
17.3%
0 12
16.0%
4 8
10.7%
9 7
9.3%
2 6
8.0%
5 6
8.0%
3 5
 
6.7%
6 4
 
5.3%
, 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 (%)
1 13
20.0%
0 12
18.5%
4 8
12.3%
9 7
10.8%
2 6
9.2%
5 6
9.2%
3 5
 
7.7%
6 4
 
6.2%
8 2
 
3.1%
7 2
 
3.1%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
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 (%)
1 13
18.1%
0 12
16.7%
4 8
11.1%
9 7
9.7%
2 6
8.3%
5 6
8.3%
3 5
 
6.9%
6 4
 
5.6%
, 4
 
5.6%
- 3
 
4.2%
Other values (2) 4
 
5.6%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 13
18.1%
0 12
16.7%
4 8
11.1%
9 7
9.7%
2 6
8.3%
5 6
8.3%
3 5
 
6.9%
6 4
 
5.6%
, 4
 
5.6%
- 3
 
4.2%
Other values (2) 4
 
5.6%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 16
Text

MISSING 

Distinct22
Distinct (%)66.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:37:47.220436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.2424242
Min length1

Characters and Unicode

Total characters74
Distinct characters15
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique17 ?
Unique (%)51.5%

Sample

1st row운암3동
2nd row5,452
3rd row13,368
4th row20
5th row15
ValueCountFrequency (%)
0 8
24.2%
6 2
 
6.1%
29 2
 
6.1%
20 2
 
6.1%
15 2
 
6.1%
39 1
 
3.0%
133 1
 
3.0%
5,448 1
 
3.0%
4 1
 
3.0%
37 1
 
3.0%
Other values (12) 12
36.4%
2024-02-10T09:37:48.234682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 11
14.9%
3 9
12.2%
2 8
10.8%
5 7
9.5%
6 7
9.5%
4 7
9.5%
1 6
8.1%
9 5
6.8%
, 4
 
5.4%
7 3
 
4.1%
Other values (5) 7
9.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 66
89.2%
Other Punctuation 4
 
5.4%
Other Letter 3
 
4.1%
Dash Punctuation 1
 
1.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 11
16.7%
3 9
13.6%
2 8
12.1%
5 7
10.6%
6 7
10.6%
4 7
10.6%
1 6
9.1%
9 5
7.6%
7 3
 
4.5%
8 3
 
4.5%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 71
95.9%
Hangul 3
 
4.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 11
15.5%
3 9
12.7%
2 8
11.3%
5 7
9.9%
6 7
9.9%
4 7
9.9%
1 6
8.5%
9 5
7.0%
, 4
 
5.6%
7 3
 
4.2%
Other values (2) 4
 
5.6%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 71
95.9%
Hangul 3
 
4.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 11
15.5%
3 9
12.7%
2 8
11.3%
5 7
9.9%
6 7
9.9%
4 7
9.9%
1 6
8.5%
9 5
7.0%
, 4
 
5.6%
7 3
 
4.2%
Other values (2) 4
 
5.6%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 17
Text

MISSING 

Distinct26
Distinct (%)78.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:37:48.822285image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.2727273
Min length1

Characters and Unicode

Total characters75
Distinct characters14
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique23 ?
Unique (%)69.7%

Sample

1st row동림동
2nd row9,890
3rd row22,881
4th row26
5th row7
ValueCountFrequency (%)
0 6
 
18.2%
59 2
 
6.1%
7 2
 
6.1%
1 2
 
6.1%
98 1
 
3.0%
178 1
 
3.0%
25 1
 
3.0%
22,859 1
 
3.0%
9,876 1
 
3.0%
22 1
 
3.0%
Other values (15) 15
45.5%
2024-02-10T09:37:49.785434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
8 10
13.3%
9 9
12.0%
0 8
10.7%
2 8
10.7%
5 7
9.3%
1 7
9.3%
7 5
6.7%
6 5
6.7%
4 5
6.7%
, 4
 
5.3%
Other values (4) 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 (%)
8 10
15.4%
9 9
13.8%
0 8
12.3%
2 8
12.3%
5 7
10.8%
1 7
10.8%
7 5
7.7%
6 5
7.7%
4 5
7.7%
3 1
 
1.5%
Other Letter
ValueCountFrequency (%)
2
66.7%
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 (%)
8 10
13.9%
9 9
12.5%
0 8
11.1%
2 8
11.1%
5 7
9.7%
1 7
9.7%
7 5
6.9%
6 5
6.9%
4 5
6.9%
, 4
 
5.6%
Other values (2) 4
 
5.6%
Hangul
ValueCountFrequency (%)
2
66.7%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
8 10
13.9%
9 9
12.5%
0 8
11.1%
2 8
11.1%
5 7
9.7%
1 7
9.7%
7 5
6.9%
6 5
6.9%
4 5
6.9%
, 4
 
5.6%
Other values (2) 4
 
5.6%
Hangul
ValueCountFrequency (%)
2
66.7%
1
33.3%

Unnamed: 18
Text

MISSING 

Distinct27
Distinct (%)81.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:37:50.390444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
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

Unique25 ?
Unique (%)75.8%

Sample

1st row우산동
2nd row6,493
3rd row12,437
4th row45
5th row7
ValueCountFrequency (%)
0 6
 
18.2%
47 2
 
6.1%
1 1
 
3.0%
146 1
 
3.0%
13,702 1
 
3.0%
6,979 1
 
3.0%
2 1
 
3.0%
1,265 1
 
3.0%
486 1
 
3.0%
12 1
 
3.0%
Other values (17) 17
51.5%
2024-02-10T09:37:51.471831image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6 12
14.5%
7 11
13.3%
1 10
12.0%
0 9
10.8%
4 9
10.8%
, 6
7.2%
9 6
7.2%
2 6
7.2%
3 5
6.0%
5 4
 
4.8%
Other values (4) 5
6.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 74
89.2%
Other Punctuation 6
 
7.2%
Other Letter 3
 
3.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
6 12
16.2%
7 11
14.9%
1 10
13.5%
0 9
12.2%
4 9
12.2%
9 6
8.1%
2 6
8.1%
3 5
6.8%
5 4
 
5.4%
8 2
 
2.7%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 6
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
6 12
15.0%
7 11
13.8%
1 10
12.5%
0 9
11.2%
4 9
11.2%
, 6
7.5%
9 6
7.5%
2 6
7.5%
3 5
6.2%
5 4
 
5.0%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
6 12
15.0%
7 11
13.8%
1 10
12.5%
0 9
11.2%
4 9
11.2%
, 6
7.5%
9 6
7.5%
2 6
7.5%
3 5
6.2%
5 4
 
5.0%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 19
Text

MISSING 

Distinct23
Distinct (%)69.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:37:51.785729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
Mean length2.0909091
Min length1

Characters and Unicode

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

Unique

Unique20 ?
Unique (%)60.6%

Sample

1st row풍향동
2nd row2,729
3rd row5,506
4th row17
5th row2
ValueCountFrequency (%)
0 8
24.2%
2 3
 
9.1%
17 2
 
6.1%
18 2
 
6.1%
45 1
 
3.0%
5,506 1
 
3.0%
2,729 1
 
3.0%
2,711 1
 
3.0%
31 1
 
3.0%
3 1
 
3.0%
Other values (12) 12
36.4%
2024-02-10T09:37:52.692934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 9
13.0%
2 9
13.0%
1 9
13.0%
7 8
11.6%
5 7
10.1%
3 6
8.7%
4 5
7.2%
, 4
5.8%
9 3
 
4.3%
6 2
 
2.9%
Other values (5) 7
10.1%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 9
15.0%
2 9
15.0%
1 9
15.0%
7 8
13.3%
5 7
11.7%
3 6
10.0%
4 5
8.3%
9 3
 
5.0%
6 2
 
3.3%
8 2
 
3.3%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
0 9
13.6%
2 9
13.6%
1 9
13.6%
7 8
12.1%
5 7
10.6%
3 6
9.1%
4 5
7.6%
, 4
6.1%
9 3
 
4.5%
6 2
 
3.0%
Other values (2) 4
6.1%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 9
13.6%
2 9
13.6%
1 9
13.6%
7 8
12.1%
5 7
10.6%
3 6
9.1%
4 5
7.6%
, 4
6.1%
9 3
 
4.5%
6 2
 
3.0%
Other values (2) 4
6.1%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 20
Text

MISSING 

Distinct26
Distinct (%)78.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:37:53.022304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.3939394
Min length1

Characters and Unicode

Total characters79
Distinct characters15
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique23 ?
Unique (%)69.7%

Sample

1st row문화동
2nd row9,629
3rd row20,324
4th row31
5th row8
ValueCountFrequency (%)
0 6
 
18.2%
8 2
 
6.1%
1 2
 
6.1%
11 2
 
6.1%
237 1
 
3.0%
114 1
 
3.0%
31 1
 
3.0%
123 1
 
3.0%
20,262 1
 
3.0%
9,610 1
 
3.0%
Other values (15) 15
45.5%
2024-02-10T09:37:53.811424image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 15
19.0%
0 13
16.5%
2 10
12.7%
3 6
 
7.6%
6 6
 
7.6%
9 5
 
6.3%
8 4
 
5.1%
7 4
 
5.1%
4 4
 
5.1%
, 4
 
5.1%
Other values (5) 8
10.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 69
87.3%
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
21.7%
0 13
18.8%
2 10
14.5%
3 6
 
8.7%
6 6
 
8.7%
9 5
 
7.2%
8 4
 
5.8%
7 4
 
5.8%
4 4
 
5.8%
5 2
 
2.9%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
1 15
19.7%
0 13
17.1%
2 10
13.2%
3 6
 
7.9%
6 6
 
7.9%
9 5
 
6.6%
8 4
 
5.3%
7 4
 
5.3%
4 4
 
5.3%
, 4
 
5.3%
Other values (2) 5
 
6.6%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 15
19.7%
0 13
17.1%
2 10
13.2%
3 6
 
7.9%
6 6
 
7.9%
9 5
 
6.6%
8 4
 
5.3%
7 4
 
5.3%
4 4
 
5.3%
, 4
 
5.3%
Other values (2) 5
 
6.6%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 21
Text

MISSING 

Distinct23
Distinct (%)69.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:37:54.160382image/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

Unique19 ?
Unique (%)57.6%

Sample

1st row문흥1동
2nd row6,432
3rd row15,459
4th row19
5th row9
ValueCountFrequency (%)
0 8
24.2%
9 2
 
6.1%
19 2
 
6.1%
45 2
 
6.1%
95 2
 
6.1%
88 1
 
3.0%
15,459 1
 
3.0%
91 1
 
3.0%
6,394 1
 
3.0%
38 1
 
3.0%
Other values (12) 12
36.4%
2024-02-10T09:37:54.934469image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 12
16.4%
9 11
15.1%
0 9
12.3%
1 8
11.0%
4 6
8.2%
8 5
6.8%
6 5
6.8%
3 5
6.8%
, 4
 
5.5%
2 2
 
2.7%
Other values (5) 6
8.2%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 12
18.8%
9 11
17.2%
0 9
14.1%
1 8
12.5%
4 6
9.4%
8 5
7.8%
6 5
7.8%
3 5
7.8%
2 2
 
3.1%
7 1
 
1.6%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
5 12
17.1%
9 11
15.7%
0 9
12.9%
1 8
11.4%
4 6
8.6%
8 5
7.1%
6 5
7.1%
3 5
7.1%
, 4
 
5.7%
2 2
 
2.9%
Other values (2) 3
 
4.3%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 12
17.1%
9 11
15.7%
0 9
12.9%
1 8
11.4%
4 6
8.6%
8 5
7.1%
6 5
7.1%
3 5
7.1%
, 4
 
5.7%
2 2
 
2.9%
Other values (2) 3
 
4.3%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 22
Text

MISSING 

Distinct27
Distinct (%)81.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:37:55.282521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.3030303
Min length1

Characters and Unicode

Total characters76
Distinct characters15
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique25 ?
Unique (%)75.8%

Sample

1st row문흥2동
2nd row7,371
3rd row15,272
4th row22
5th row5
ValueCountFrequency (%)
0 6
 
18.2%
1 2
 
6.1%
5 2
 
6.1%
93 1
 
3.0%
189 1
 
3.0%
15,244 1
 
3.0%
7,368 1
 
3.0%
28 1
 
3.0%
3 1
 
3.0%
10 1
 
3.0%
Other values (16) 16
48.5%
2024-02-10T09:37:56.052346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 10
13.2%
2 10
13.2%
0 8
10.5%
7 8
10.5%
3 7
9.2%
5 5
6.6%
8 5
6.6%
4 5
6.6%
9 5
6.6%
, 4
 
5.3%
Other values (5) 9
11.8%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 10
15.2%
2 10
15.2%
0 8
12.1%
7 8
12.1%
3 7
10.6%
5 5
7.6%
8 5
7.6%
4 5
7.6%
9 5
7.6%
6 3
 
4.5%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
1 10
13.7%
2 10
13.7%
0 8
11.0%
7 8
11.0%
3 7
9.6%
5 5
6.8%
8 5
6.8%
4 5
6.8%
9 5
6.8%
, 4
 
5.5%
Other values (2) 6
8.2%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 10
13.7%
2 10
13.7%
0 8
11.0%
7 8
11.0%
3 7
9.6%
5 5
6.8%
8 5
6.8%
4 5
6.8%
9 5
6.8%
, 4
 
5.5%
Other values (2) 6
8.2%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 23
Text

MISSING 

Distinct24
Distinct (%)72.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:37:56.425106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length2.1515152
Min length1

Characters and Unicode

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

Unique

Unique21 ?
Unique (%)63.6%

Sample

1st row두암1동
2nd row3,974
3rd row7,515
4th row10
5th row8
ValueCountFrequency (%)
0 8
24.2%
39 2
 
6.1%
8 2
 
6.1%
26 1
 
3.0%
64 1
 
3.0%
7,469 1
 
3.0%
3,944 1
 
3.0%
1 1
 
3.0%
46 1
 
3.0%
30 1
 
3.0%
Other values (14) 14
42.4%
2024-02-10T09:37:57.172049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 10
14.1%
1 10
14.1%
6 8
11.3%
3 7
9.9%
9 6
8.5%
7 6
8.5%
4 6
8.5%
, 4
 
5.6%
8 3
 
4.2%
5 3
 
4.2%
Other values (5) 8
11.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 62
87.3%
Other Punctuation 4
 
5.6%
Other Letter 3
 
4.2%
Dash Punctuation 2
 
2.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 10
16.1%
1 10
16.1%
6 8
12.9%
3 7
11.3%
9 6
9.7%
7 6
9.7%
4 6
9.7%
8 3
 
4.8%
5 3
 
4.8%
2 3
 
4.8%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
0 10
14.7%
1 10
14.7%
6 8
11.8%
3 7
10.3%
9 6
8.8%
7 6
8.8%
4 6
8.8%
, 4
 
5.9%
8 3
 
4.4%
5 3
 
4.4%
Other values (2) 5
7.4%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 10
14.7%
1 10
14.7%
6 8
11.8%
3 7
10.3%
9 6
8.8%
7 6
8.8%
4 6
8.8%
, 4
 
5.9%
8 3
 
4.4%
5 3
 
4.4%
Other values (2) 5
7.4%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 24
Text

MISSING 

Distinct27
Distinct (%)81.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:37:57.523396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.3636364
Min length1

Characters and Unicode

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

Unique

Unique25 ?
Unique (%)75.8%

Sample

1st row두암2동
2nd row7,661
3rd row15,605
4th row47
5th row9
ValueCountFrequency (%)
0 6
 
18.2%
9 2
 
6.1%
1 2
 
6.1%
100 1
 
3.0%
15,545 1
 
3.0%
7,633 1
 
3.0%
60 1
 
3.0%
28 1
 
3.0%
8 1
 
3.0%
39 1
 
3.0%
Other values (16) 16
48.5%
2024-02-10T09:37:58.419366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 14
17.9%
1 10
12.8%
6 8
10.3%
5 8
10.3%
7 7
9.0%
8 5
 
6.4%
3 5
 
6.4%
2 4
 
5.1%
, 4
 
5.1%
4 4
 
5.1%
Other values (5) 9
11.5%

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 (%)
0 14
20.6%
1 10
14.7%
6 8
11.8%
5 8
11.8%
7 7
10.3%
8 5
 
7.4%
3 5
 
7.4%
2 4
 
5.9%
4 4
 
5.9%
9 3
 
4.4%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
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 (%)
0 14
18.7%
1 10
13.3%
6 8
10.7%
5 8
10.7%
7 7
9.3%
8 5
 
6.7%
3 5
 
6.7%
2 4
 
5.3%
, 4
 
5.3%
4 4
 
5.3%
Other values (2) 6
8.0%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 14
18.7%
1 10
13.3%
6 8
10.7%
5 8
10.7%
7 7
9.3%
8 5
 
6.7%
3 5
 
6.7%
2 4
 
5.3%
, 4
 
5.3%
4 4
 
5.3%
Other values (2) 6
8.0%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 25
Text

MISSING 

Distinct21
Distinct (%)63.6%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:37:58.886455image/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

Unique15 ?
Unique (%)45.5%

Sample

1st row두암3동
2nd row7,694
3rd row12,893
4th row24
5th row8
ValueCountFrequency (%)
0 7
21.2%
24 3
 
9.1%
8 2
 
6.1%
1 2
 
6.1%
32 2
 
6.1%
7,694 2
 
6.1%
49 1
 
3.0%
112 1
 
3.0%
57 1
 
3.0%
55 1
 
3.0%
Other values (11) 11
33.3%
2024-02-10T09:37:59.874377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 12
16.4%
1 10
13.7%
0 9
12.3%
4 7
9.6%
3 7
9.6%
8 5
6.8%
9 5
6.8%
5 5
6.8%
, 4
 
5.5%
7 3
 
4.1%
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 (%)
2 12
18.5%
1 10
15.4%
0 9
13.8%
4 7
10.8%
3 7
10.8%
8 5
7.7%
9 5
7.7%
5 5
7.7%
7 3
 
4.6%
6 2
 
3.1%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
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 (%)
2 12
17.1%
1 10
14.3%
0 9
12.9%
4 7
10.0%
3 7
10.0%
8 5
7.1%
9 5
7.1%
5 5
7.1%
, 4
 
5.7%
7 3
 
4.3%
Other values (2) 3
 
4.3%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 12
17.1%
1 10
14.3%
0 9
12.9%
4 7
10.0%
3 7
10.0%
8 5
7.1%
9 5
7.1%
5 5
7.1%
, 4
 
5.7%
7 3
 
4.3%
Other values (2) 3
 
4.3%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 26
Text

MISSING 

Distinct24
Distinct (%)72.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:38:00.312893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.2121212
Min length1

Characters and Unicode

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

Unique

Unique21 ?
Unique (%)63.6%

Sample

1st row삼각동
2nd row6,032
3rd row13,736
4th row24
5th row4
ValueCountFrequency (%)
0 8
24.2%
24 2
 
6.1%
4 2
 
6.1%
79 1
 
3.0%
13,736 1
 
3.0%
92 1
 
3.0%
6,018 1
 
3.0%
37 1
 
3.0%
14 1
 
3.0%
5 1
 
3.0%
Other values (14) 14
42.4%
2024-02-10T09:38:01.251597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

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

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 10
15.6%
4 9
14.1%
1 8
12.5%
3 7
10.9%
2 6
9.4%
6 6
9.4%
7 5
7.8%
9 5
7.8%
5 4
 
6.2%
8 4
 
6.2%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
0 10
14.3%
4 9
12.9%
1 8
11.4%
3 7
10.0%
2 6
8.6%
6 6
8.6%
7 5
7.1%
9 5
7.1%
5 4
 
5.7%
8 4
 
5.7%
Other values (2) 6
8.6%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 10
14.3%
4 9
12.9%
1 8
11.4%
3 7
10.0%
2 6
8.6%
6 6
8.6%
7 5
7.1%
9 5
7.1%
5 4
 
5.7%
8 4
 
5.7%
Other values (2) 6
8.6%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 27
Text

MISSING 

Distinct26
Distinct (%)78.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:38:01.713854image/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

Unique24 ?
Unique (%)72.7%

Sample

1st row일곡동
2nd row11,507
3rd row29,016
4th row24
5th row12
ValueCountFrequency (%)
0 7
21.2%
12 3
 
9.1%
131 1
 
3.0%
144 1
 
3.0%
28,975 1
 
3.0%
11,495 1
 
3.0%
1 1
 
3.0%
41 1
 
3.0%
13 1
 
3.0%
78 1
 
3.0%
Other values (15) 15
45.5%
2024-02-10T09:38:02.629834image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 19
22.6%
0 11
13.1%
2 10
11.9%
5 9
10.7%
4 7
 
8.3%
7 5
 
6.0%
3 5
 
6.0%
, 4
 
4.8%
9 3
 
3.6%
6 3
 
3.6%
Other values (5) 8
9.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 75
89.3%
Other Punctuation 4
 
4.8%
Other Letter 3
 
3.6%
Dash Punctuation 2
 
2.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 19
25.3%
0 11
14.7%
2 10
13.3%
5 9
12.0%
4 7
 
9.3%
7 5
 
6.7%
3 5
 
6.7%
9 3
 
4.0%
6 3
 
4.0%
8 3
 
4.0%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
1 19
23.5%
0 11
13.6%
2 10
12.3%
5 9
11.1%
4 7
 
8.6%
7 5
 
6.2%
3 5
 
6.2%
, 4
 
4.9%
9 3
 
3.7%
6 3
 
3.7%
Other values (2) 5
 
6.2%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 19
23.5%
0 11
13.6%
2 10
12.3%
5 9
11.1%
4 7
 
8.6%
7 5
 
6.2%
3 5
 
6.2%
, 4
 
4.9%
9 3
 
3.7%
6 3
 
3.7%
Other values (2) 5
 
6.2%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 28
Text

MISSING 

Distinct23
Distinct (%)69.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:38:03.031124image/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

Unique19 ?
Unique (%)57.6%

Sample

1st row매곡동
2nd row5,496
3rd row13,621
4th row11
5th row6
ValueCountFrequency (%)
0 7
21.2%
6 3
 
9.1%
67 2
 
6.1%
5 2
 
6.1%
11 2
 
6.1%
2 1
 
3.0%
76 1
 
3.0%
13,621 1
 
3.0%
143 1
 
3.0%
5,491 1
 
3.0%
Other values (12) 12
36.4%
2024-02-10T09:38:03.963187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 12
16.7%
6 9
12.5%
0 8
11.1%
2 6
8.3%
5 6
8.3%
3 6
8.3%
7 5
6.9%
9 5
6.9%
4 4
 
5.6%
, 4
 
5.6%
Other values (5) 7
9.7%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 12
19.0%
6 9
14.3%
0 8
12.7%
2 6
9.5%
5 6
9.5%
3 6
9.5%
7 5
7.9%
9 5
7.9%
4 4
 
6.3%
8 2
 
3.2%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
1 12
17.4%
6 9
13.0%
0 8
11.6%
2 6
8.7%
5 6
8.7%
3 6
8.7%
7 5
7.2%
9 5
7.2%
4 4
 
5.8%
, 4
 
5.8%
Other values (2) 4
 
5.8%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 12
17.4%
6 9
13.0%
0 8
11.6%
2 6
8.7%
5 6
8.7%
3 6
8.7%
7 5
7.2%
9 5
7.2%
4 4
 
5.8%
, 4
 
5.8%
Other values (2) 4
 
5.8%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 29
Text

MISSING 

Distinct23
Distinct (%)69.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:38:04.356595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.2424242
Min length1

Characters and Unicode

Total characters74
Distinct characters15
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique19 ?
Unique (%)57.6%

Sample

1st row오치1동
2nd row5,453
3rd row10,567
4th row23
5th row9
ValueCountFrequency (%)
0 8
24.2%
9 2
 
6.1%
23 2
 
6.1%
4 2
 
6.1%
96 1
 
3.0%
10,567 1
 
3.0%
82 1
 
3.0%
5,426 1
 
3.0%
49 1
 
3.0%
27 1
 
3.0%
Other values (13) 13
39.4%
2024-02-10T09:38:05.298835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 12
16.2%
5 10
13.5%
2 8
10.8%
3 7
9.5%
1 7
9.5%
4 5
6.8%
9 5
6.8%
7 4
 
5.4%
, 4
 
5.4%
6 4
 
5.4%
Other values (5) 8
10.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 65
87.8%
Other Punctuation 4
 
5.4%
Other Letter 3
 
4.1%
Dash Punctuation 2
 
2.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 12
18.5%
5 10
15.4%
2 8
12.3%
3 7
10.8%
1 7
10.8%
4 5
7.7%
9 5
7.7%
7 4
 
6.2%
6 4
 
6.2%
8 3
 
4.6%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 71
95.9%
Hangul 3
 
4.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 12
16.9%
5 10
14.1%
2 8
11.3%
3 7
9.9%
1 7
9.9%
4 5
7.0%
9 5
7.0%
7 4
 
5.6%
, 4
 
5.6%
6 4
 
5.6%
Other values (2) 5
7.0%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 71
95.9%
Hangul 3
 
4.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 12
16.9%
5 10
14.1%
2 8
11.3%
3 7
9.9%
1 7
9.9%
4 5
7.0%
9 5
7.0%
7 4
 
5.6%
, 4
 
5.6%
6 4
 
5.6%
Other values (2) 5
7.0%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 30
Text

MISSING 

Distinct23
Distinct (%)69.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:38:05.799001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.3333333
Min length1

Characters and Unicode

Total characters77
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 row오치2동
2nd row6,922
3rd row12,092
4th row26
5th row10
ValueCountFrequency (%)
0 8
24.2%
10 2
 
6.1%
63 2
 
6.1%
26 2
 
6.1%
71 1
 
3.0%
67 1
 
3.0%
6,909 1
 
3.0%
17 1
 
3.0%
13 1
 
3.0%
11 1
 
3.0%
Other values (13) 13
39.4%
2024-02-10T09:38:06.903872image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 14
18.2%
2 11
14.3%
1 11
14.3%
6 10
13.0%
3 9
11.7%
9 5
 
6.5%
, 4
 
5.2%
7 4
 
5.2%
5 3
 
3.9%
- 2
 
2.6%
Other values (4) 4
 
5.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 68
88.3%
Other Punctuation 4
 
5.2%
Other Letter 3
 
3.9%
Dash Punctuation 2
 
2.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 14
20.6%
2 11
16.2%
1 11
16.2%
6 10
14.7%
3 9
13.2%
9 5
 
7.4%
7 4
 
5.9%
5 3
 
4.4%
8 1
 
1.5%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 74
96.1%
Hangul 3
 
3.9%

Most frequent character per script

Common
ValueCountFrequency (%)
0 14
18.9%
2 11
14.9%
1 11
14.9%
6 10
13.5%
3 9
12.2%
9 5
 
6.8%
, 4
 
5.4%
7 4
 
5.4%
5 3
 
4.1%
- 2
 
2.7%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 74
96.1%
Hangul 3
 
3.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 14
18.9%
2 11
14.9%
1 11
14.9%
6 10
13.5%
3 9
12.2%
9 5
 
6.8%
, 4
 
5.4%
7 4
 
5.4%
5 3
 
4.1%
- 2
 
2.7%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 31
Text

MISSING 

Distinct22
Distinct (%)66.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:38:07.328529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
Mean length1.969697
Min length1

Characters and Unicode

Total characters65
Distinct characters14
Distinct categories4 ?
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 row석곡동
2nd row1,353
3rd row2,438
4th row11
5th row3
ValueCountFrequency (%)
0 6
18.2%
5 3
 
9.1%
1 3
 
9.1%
11 2
 
6.1%
12 2
 
6.1%
4 2
 
6.1%
10 2
 
6.1%
3 2
 
6.1%
30 1
 
3.0%
8 1
 
3.0%
Other values (9) 9
27.3%
2024-02-10T09:38:08.631808image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 17
26.2%
0 9
13.8%
3 8
12.3%
2 6
 
9.2%
5 5
 
7.7%
4 5
 
7.7%
, 4
 
6.2%
- 3
 
4.6%
8 2
 
3.1%
9 2
 
3.1%
Other values (4) 4
 
6.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 55
84.6%
Other Punctuation 4
 
6.2%
Dash Punctuation 3
 
4.6%
Other Letter 3
 
4.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 17
30.9%
0 9
16.4%
3 8
14.5%
2 6
 
10.9%
5 5
 
9.1%
4 5
 
9.1%
8 2
 
3.6%
9 2
 
3.6%
6 1
 
1.8%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
1 17
27.4%
0 9
14.5%
3 8
12.9%
2 6
 
9.7%
5 5
 
8.1%
4 5
 
8.1%
, 4
 
6.5%
- 3
 
4.8%
8 2
 
3.2%
9 2
 
3.2%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 17
27.4%
0 9
14.5%
3 8
12.9%
2 6
 
9.7%
5 5
 
8.1%
4 5
 
8.1%
, 4
 
6.5%
- 3
 
4.8%
8 2
 
3.2%
9 2
 
3.2%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 32
Text

MISSING 

Distinct24
Distinct (%)72.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:38:08.975919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.3636364
Min length1

Characters and Unicode

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

Unique

Unique21 ?
Unique (%)63.6%

Sample

1st row건국동
2nd row9,061
3rd row21,839
4th row52
5th row9
ValueCountFrequency (%)
0 7
21.2%
9 3
 
9.1%
87 2
 
6.1%
102 1
 
3.0%
105 1
 
3.0%
21,813 1
 
3.0%
9,044 1
 
3.0%
1 1
 
3.0%
26 1
 
3.0%
17 1
 
3.0%
Other values (14) 14
42.4%
2024-02-10T09:38:09.887751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 14
17.9%
1 11
14.1%
9 9
11.5%
2 9
11.5%
8 6
7.7%
5 5
 
6.4%
4 5
 
6.4%
7 4
 
5.1%
, 4
 
5.1%
3 3
 
3.8%
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 (%)
0 14
20.6%
1 11
16.2%
9 9
13.2%
2 9
13.2%
8 6
8.8%
5 5
 
7.4%
4 5
 
7.4%
7 4
 
5.9%
3 3
 
4.4%
6 2
 
2.9%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
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 (%)
0 14
18.7%
1 11
14.7%
9 9
12.0%
2 9
12.0%
8 6
8.0%
5 5
 
6.7%
4 5
 
6.7%
7 4
 
5.3%
, 4
 
5.3%
3 3
 
4.0%
Other values (2) 5
 
6.7%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 14
18.7%
1 11
14.7%
9 9
12.0%
2 9
12.0%
8 6
8.0%
5 5
 
6.7%
4 5
 
6.7%
7 4
 
5.3%
, 4
 
5.3%
3 3
 
4.0%
Other values (2) 5
 
6.7%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 33
Text

MISSING 

Distinct26
Distinct (%)78.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:38:10.473850image/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

Unique23 ?
Unique (%)69.7%

Sample

1st row양산동
2nd row16,327
3rd row37,121
4th row63
5th row17
ValueCountFrequency (%)
0 6
 
18.2%
1 2
 
6.1%
17 2
 
6.1%
165 1
 
3.0%
175 1
 
3.0%
37,089 1
 
3.0%
16,302 1
 
3.0%
32 1
 
3.0%
25 1
 
3.0%
10 1
 
3.0%
Other values (16) 16
48.5%
2024-02-10T09:38:11.594049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 18
20.7%
0 14
16.1%
3 11
12.6%
2 9
10.3%
7 7
 
8.0%
6 6
 
6.9%
5 5
 
5.7%
, 4
 
4.6%
9 3
 
3.4%
8 3
 
3.4%
Other values (5) 7
 
8.0%

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 18
23.1%
0 14
17.9%
3 11
14.1%
2 9
11.5%
7 7
 
9.0%
6 6
 
7.7%
5 5
 
6.4%
9 3
 
3.8%
8 3
 
3.8%
4 2
 
2.6%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
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 18
21.4%
0 14
16.7%
3 11
13.1%
2 9
10.7%
7 7
 
8.3%
6 6
 
7.1%
5 5
 
6.0%
, 4
 
4.8%
9 3
 
3.6%
8 3
 
3.6%
Other values (2) 4
 
4.8%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 18
21.4%
0 14
16.7%
3 11
13.1%
2 9
10.7%
7 7
 
8.3%
6 6
 
7.1%
5 5
 
6.0%
, 4
 
4.8%
9 3
 
3.6%
8 3
 
3.6%
Other values (2) 4
 
4.8%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 34
Text

MISSING 

Distinct23
Distinct (%)69.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:38:11.945995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length3
Mean length2.3030303
Min length1

Characters and Unicode

Total characters76
Distinct characters15
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique21 ?
Unique (%)63.6%

Sample

1st row신용동
2nd row11,814
3rd row29,358
4th row9
5th row9
ValueCountFrequency (%)
0 8
24.2%
9 5
15.2%
235 1
 
3.0%
11,805 1
 
3.0%
28 1
 
3.0%
5 1
 
3.0%
89 1
 
3.0%
60 1
 
3.0%
86 1
 
3.0%
121 1
 
3.0%
Other values (12) 12
36.4%
2024-02-10T09:38:12.966427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 14
18.4%
0 12
15.8%
9 12
15.8%
8 6
7.9%
2 6
7.9%
3 6
7.9%
5 5
 
6.6%
, 4
 
5.3%
6 3
 
3.9%
4 2
 
2.6%
Other values (5) 6
7.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 67
88.2%
Other Punctuation 4
 
5.3%
Other Letter 3
 
3.9%
Dash Punctuation 2
 
2.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 14
20.9%
0 12
17.9%
9 12
17.9%
8 6
9.0%
2 6
9.0%
3 6
9.0%
5 5
 
7.5%
6 3
 
4.5%
4 2
 
3.0%
7 1
 
1.5%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
1 14
19.2%
0 12
16.4%
9 12
16.4%
8 6
8.2%
2 6
8.2%
3 6
8.2%
5 5
 
6.8%
, 4
 
5.5%
6 3
 
4.1%
4 2
 
2.7%
Other values (2) 3
 
4.1%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 14
19.2%
0 12
16.4%
9 12
16.4%
8 6
8.2%
2 6
8.2%
3 6
8.2%
5 5
 
6.8%
, 4
 
5.5%
6 3
 
4.1%
4 2
 
2.7%
Other values (2) 3
 
4.1%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
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: 27Unnamed: 28Unnamed: 29Unnamed: 30Unnamed: 31Unnamed: 32Unnamed: 33Unnamed: 34
0<NA>행정기관 :<NA>광주광역시 북구<NA><NA><NA><NA><NA><NA>출력일자 :<NA>2022.12.12<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
1<NA>작성기준 :<NA>2022.11 현재<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
2<NA>시, 군, 구(읍면동)<NA><NA><NA>합 계중흥1동중흥2동중흥3동중앙동임동신안동<NA>용봉동운암1동운암2동운암3동동림동우산동풍향동문화동문흥1동문흥2동두암1동두암2동두암3동삼각동일곡동매곡동오치1동오치2동석곡동건국동양산동신용동
3<NA>전월말세대수<NA><NA><NA>198,0232,9474,4143,6342,3374,6347,469<NA>17,8317,4296,0385,4529,8906,4932,7299,6296,4327,3713,9747,6617,6946,03211,5075,4965,4536,9221,3539,06116,32711,814
4<NA>전월말인구수<NA><NA><NA>424,7204,6238,4786,5503,9759,13712,598<NA>37,73618,97511,60013,36822,88112,4375,50620,32415,45915,2727,51515,60512,89313,73629,01613,62110,56712,0922,43821,83937,12129,358
5<NA>전월말거주불명자수<NA><NA><NA>883422446272663<NA>8118522026451731192210472424241123261152639
6<NA>전월말재외국민등록자수<NA><NA><NA>224063551<NA>2018915772895898412691039179
7<NA>증 가 요 인전 입<NA>5,2046511813173115179<NA>382108921331441,41667174951637615511214124210910912821170293193
8<NA><NA><NA>남자<NA>2,621346272376086<NA>193594567697063280508437855775106625763138315592
9<NA><NA><NA>여자<NA>2,583315659365593<NA>189494766757103594457939705566136475265887138101
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: 27Unnamed: 28Unnamed: 29Unnamed: 30Unnamed: 31Unnamed: 32Unnamed: 33Unnamed: 34
25<NA><NA>말소<NA><NA>2000000<NA>0000000000010000000010
26<NA><NA>국외<NA><NA>0000000<NA>0000000000000000000000
27<NA><NA>기타<NA><NA>0000000<NA>0000000000000000000000
28<NA>세대수증감<NA><NA><NA>35-31-32-35-28-116<NA>5-14-31-4-14486-18-19-38-3-30-280-14-12-5-27-13-4-17-25-9
29<NA>인구수증감<NA><NA><NA>281-30-53-35-17-22-33<NA>-86-48-5929-221,265-31-62-95-28-46-60-11-37-41-33-49-17-12-26-32-28
30<NA>거주불명자수증감<NA><NA><NA>-7-12-6-10-1<NA>20-10-120-10-11-1001000-1-110
31<NA>금월말세대수<NA><NA><NA>198,0582,9164,3823,5992,3094,6237,475<NA>17,8367,4156,0075,4489,8766,9792,7119,6106,3947,3683,9447,6337,6946,01811,4955,4915,4266,9091,3499,04416,30211,805
32<NA>금월말인구수<NA><NA><NA>425,0014,5938,4256,5153,9589,11512,565<NA>37,65018,92711,54113,39722,85913,7025,47520,26215,36415,2447,46915,54512,88213,69928,97513,58810,51812,0752,42621,81337,08929,330
33<NA>금월말거주불명자수<NA><NA><NA>876412640262662<NA>8318512025471730192111462424251123261051649
34<NA>금월말재외국민등록자수<NA><NA><NA>226062651<NA>2018915882895898412691039179

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: 27Unnamed: 28Unnamed: 29Unnamed: 30Unnamed: 31Unnamed: 32Unnamed: 33Unnamed: 34# duplicates
0<NA>기타<NA><NA>0000000<NA>00000000000000000000002