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

Description2023-09-14
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 09:53:26.092190
Analysis finished2024-02-10 09:53:27.790982
Duration1.7 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
2024-02-10T09:53:28.003104image/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%
2024-02-10T09:53:29.150890image/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
2024-02-10T09:53:29.611318image/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%
2024-02-10T09:53:30.723886image/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
2024-02-10T09:53:31.240180image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length9
Mean length3.4166667
Min length1

Characters and Unicode

Total characters41
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 북구
2nd row2023.07 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%
2023.07 1
7.1%
현재 1
7.1%
2024-02-10T09:53:32.277812image/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
 
4.9%
2
 
4.9%
2
 
4.9%
2
 
4.9%
2
 
4.9%
2
 
4.9%
Other values (11) 13
31.7%

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 2
33.3%
0 2
33.3%
3 1
16.7%
7 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 2
20.0%
0 2
20.0%
3 1
 
10.0%
7 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 2
20.0%
0 2
20.0%
3 1
 
10.0%
7 1
 
10.0%
. 1
 
10.0%

Unnamed: 4
Text

MISSING 

Distinct2
Distinct (%)50.0%
Missing31
Missing (%)88.6%
Memory size412.0 B
2024-02-10T09:53:32.668358image/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%
2024-02-10T09:53:33.833451image/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 

Distinct28
Distinct (%)84.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:53:34.434032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length3.9393939
Min length1

Characters and Unicode

Total characters130
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 row198,806
3rd row422,629
4th row1,020
5th row238
ValueCountFrequency (%)
0 4
 
11.8%
1,372 2
 
5.9%
238 2
 
5.9%
1,764 1
 
2.9%
3,673 1
 
2.9%
422,475 1
 
2.9%
198,872 1
 
2.9%
9 1
 
2.9%
154 1
 
2.9%
66 1
 
2.9%
Other values (19) 19
55.9%
2024-02-10T09:53:35.707219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 22
16.9%
, 18
13.8%
2 17
13.1%
0 11
8.5%
3 11
8.5%
7 10
7.7%
6 8
 
6.2%
8 7
 
5.4%
5 7
 
5.4%
9 7
 
5.4%
Other values (5) 12
9.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 106
81.5%
Other Punctuation 18
 
13.8%
Space Separator 2
 
1.5%
Dash Punctuation 2
 
1.5%
Other Letter 2
 
1.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 22
20.8%
2 17
16.0%
0 11
10.4%
3 11
10.4%
7 10
9.4%
6 8
 
7.5%
8 7
 
6.6%
5 7
 
6.6%
9 7
 
6.6%
4 6
 
5.7%
Other Letter
ValueCountFrequency (%)
1
50.0%
1
50.0%
Other Punctuation
ValueCountFrequency (%)
, 18
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 128
98.5%
Hangul 2
 
1.5%

Most frequent character per script

Common
ValueCountFrequency (%)
1 22
17.2%
, 18
14.1%
2 17
13.3%
0 11
8.6%
3 11
8.6%
7 10
7.8%
6 8
 
6.2%
8 7
 
5.5%
5 7
 
5.5%
9 7
 
5.5%
Other values (3) 10
7.8%
Hangul
ValueCountFrequency (%)
1
50.0%
1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 128
98.5%
Hangul 2
 
1.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 22
17.2%
, 18
14.1%
2 17
13.3%
0 11
8.6%
3 11
8.6%
7 10
7.8%
6 8
 
6.2%
8 7
 
5.5%
5 7
 
5.5%
9 7
 
5.5%
Other values (3) 10
7.8%
Hangul
ValueCountFrequency (%)
1
50.0%
1
50.0%

Unnamed: 6
Text

MISSING 

Distinct18
Distinct (%)54.5%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:53:36.323624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length2
Min length1

Characters and Unicode

Total characters66
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

Unique12 ?
Unique (%)36.4%

Sample

1st row중흥1동
2nd row2,910
3rd row4,550
4th row47
5th row2
ValueCountFrequency (%)
0 7
21.2%
33 4
12.1%
1 4
12.1%
2 2
 
6.1%
66 2
 
6.1%
22 2
 
6.1%
24 1
 
3.0%
21 1
 
3.0%
4,551 1
 
3.0%
8 1
 
3.0%
Other values (8) 8
24.2%
2024-02-10T09:53:37.280714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 12
18.2%
0 10
15.2%
1 9
13.6%
3 9
13.6%
4 5
7.6%
6 4
 
6.1%
, 4
 
6.1%
5 4
 
6.1%
8 3
 
4.5%
9 2
 
3.0%
Other values (4) 4
 
6.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 59
89.4%
Other Punctuation 4
 
6.1%
Other Letter 3
 
4.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 12
20.3%
0 10
16.9%
1 9
15.3%
3 9
15.3%
4 5
8.5%
6 4
 
6.8%
5 4
 
6.8%
8 3
 
5.1%
9 2
 
3.4%
7 1
 
1.7%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 63
95.5%
Hangul 3
 
4.5%

Most frequent character per script

Common
ValueCountFrequency (%)
2 12
19.0%
0 10
15.9%
1 9
14.3%
3 9
14.3%
4 5
7.9%
6 4
 
6.3%
, 4
 
6.3%
5 4
 
6.3%
8 3
 
4.8%
9 2
 
3.2%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 63
95.5%
Hangul 3
 
4.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 12
19.0%
0 10
15.9%
1 9
14.3%
3 9
14.3%
4 5
7.9%
6 4
 
6.3%
, 4
 
6.3%
5 4
 
6.3%
8 3
 
4.8%
9 2
 
3.2%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 7
Text

MISSING 

Distinct26
Distinct (%)78.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:53:37.708945image/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

Unique23 ?
Unique (%)69.7%

Sample

1st row중흥2동
2nd row4,425
3rd row8,414
4th row33
5th row7
ValueCountFrequency (%)
0 6
 
18.2%
1 3
 
9.1%
7 2
 
6.1%
18 1
 
3.0%
33 1
 
3.0%
48 1
 
3.0%
8,413 1
 
3.0%
4,444 1
 
3.0%
2 1
 
3.0%
19 1
 
3.0%
Other values (15) 15
45.5%
2024-02-10T09:53:38.650866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4 11
15.7%
1 10
14.3%
0 8
11.4%
5 6
8.6%
2 6
8.6%
7 5
7.1%
8 5
7.1%
3 5
7.1%
, 4
 
5.7%
9 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 (%)
4 11
18.0%
1 10
16.4%
0 8
13.1%
5 6
9.8%
2 6
9.8%
7 5
8.2%
8 5
8.2%
3 5
8.2%
9 4
 
6.6%
6 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 67
95.7%
Hangul 3
 
4.3%

Most frequent character per script

Common
ValueCountFrequency (%)
4 11
16.4%
1 10
14.9%
0 8
11.9%
5 6
9.0%
2 6
9.0%
7 5
7.5%
8 5
7.5%
3 5
7.5%
, 4
 
6.0%
9 4
 
6.0%
Other values (2) 3
 
4.5%
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 (%)
4 11
16.4%
1 10
14.9%
0 8
11.9%
5 6
9.0%
2 6
9.0%
7 5
7.5%
8 5
7.5%
3 5
7.5%
, 4
 
6.0%
9 4
 
6.0%
Other values (2) 3
 
4.5%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 8
Text

MISSING 

Distinct24
Distinct (%)72.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:53:39.026938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length2.0606061
Min length1

Characters and Unicode

Total characters68
Distinct characters15
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique20 ?
Unique (%)60.6%

Sample

1st row중흥3동
2nd row3,709
3rd row6,603
4th row41
5th row3
ValueCountFrequency (%)
0 6
18.2%
3 4
 
12.1%
39 2
 
6.1%
43 2
 
6.1%
2 2
 
6.1%
27 1
 
3.0%
41 1
 
3.0%
85 1
 
3.0%
3,706 1
 
3.0%
5 1
 
3.0%
Other values (12) 12
36.4%
2024-02-10T09:53:39.901310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 14
20.6%
0 10
14.7%
6 7
10.3%
2 6
8.8%
4 5
 
7.4%
, 4
 
5.9%
7 4
 
5.9%
1 4
 
5.9%
9 3
 
4.4%
8 3
 
4.4%
Other values (5) 8
11.8%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 14
23.7%
0 10
16.9%
6 7
11.9%
2 6
10.2%
4 5
 
8.5%
7 4
 
6.8%
1 4
 
6.8%
9 3
 
5.1%
8 3
 
5.1%
5 3
 
5.1%
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 65
95.6%
Hangul 3
 
4.4%

Most frequent character per script

Common
ValueCountFrequency (%)
3 14
21.5%
0 10
15.4%
6 7
10.8%
2 6
9.2%
4 5
 
7.7%
, 4
 
6.2%
7 4
 
6.2%
1 4
 
6.2%
9 3
 
4.6%
8 3
 
4.6%
Other values (2) 5
 
7.7%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 14
21.5%
0 10
15.4%
6 7
10.8%
2 6
9.2%
4 5
 
7.7%
, 4
 
6.2%
7 4
 
6.2%
1 4
 
6.2%
9 3
 
4.6%
8 3
 
4.6%
Other values (2) 5
 
7.7%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 9
Text

MISSING 

Distinct22
Distinct (%)66.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:53:40.418532image/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

Unique16 ?
Unique (%)48.5%

Sample

1st row중앙동
2nd row2,273
3rd row3,928
4th row34
5th row5
ValueCountFrequency (%)
0 7
21.2%
5 2
 
6.1%
4 2
 
6.1%
21 2
 
6.1%
1 2
 
6.1%
34 2
 
6.1%
8 1
 
3.0%
38 1
 
3.0%
2,254 1
 
3.0%
28 1
 
3.0%
Other values (12) 12
36.4%
2024-02-10T09:53:41.310686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 11
16.4%
3 10
14.9%
2 9
13.4%
1 9
13.4%
4 5
7.5%
8 5
7.5%
5 4
 
6.0%
9 4
 
6.0%
, 4
 
6.0%
- 2
 
3.0%
Other values (4) 4
 
6.0%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 11
19.0%
3 10
17.2%
2 9
15.5%
1 9
15.5%
4 5
8.6%
8 5
8.6%
5 4
 
6.9%
9 4
 
6.9%
7 1
 
1.7%
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 64
95.5%
Hangul 3
 
4.5%

Most frequent character per script

Common
ValueCountFrequency (%)
0 11
17.2%
3 10
15.6%
2 9
14.1%
1 9
14.1%
4 5
7.8%
8 5
7.8%
5 4
 
6.2%
9 4
 
6.2%
, 4
 
6.2%
- 2
 
3.1%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 11
17.2%
3 10
15.6%
2 9
14.1%
1 9
14.1%
4 5
7.8%
8 5
7.8%
5 4
 
6.2%
9 4
 
6.2%
, 4
 
6.2%
- 2
 
3.1%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 10
Text

MISSING 

Distinct24
Distinct (%)70.6%
Missing1
Missing (%)2.9%
Memory size412.0 B
2024-02-10T09:53:41.649283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.2058824
Min length1

Characters and Unicode

Total characters75
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

Unique20 ?
Unique (%)58.8%

Sample

1st row출력일자 :
2nd row임동
3rd row4,617
4th row9,165
5th row28
ValueCountFrequency (%)
0 7
20.0%
5 3
 
8.6%
28 2
 
5.7%
16 2
 
5.7%
출력일자 1
 
2.9%
98 1
 
2.9%
9,149 1
 
2.9%
4,601 1
 
2.9%
1 1
 
2.9%
35 1
 
2.9%
Other values (15) 15
42.9%
2024-02-10T09:53:42.604751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 11
14.7%
1 9
12.0%
4 8
10.7%
2 6
8.0%
6 6
8.0%
5 6
8.0%
8 5
6.7%
9 5
6.7%
, 4
 
5.3%
- 3
 
4.0%
Other values (10) 12
16.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 60
80.0%
Other Letter 6
 
8.0%
Other Punctuation 5
 
6.7%
Dash Punctuation 3
 
4.0%
Space Separator 1
 
1.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 11
18.3%
1 9
15.0%
4 8
13.3%
2 6
10.0%
6 6
10.0%
5 6
10.0%
8 5
8.3%
9 5
8.3%
7 2
 
3.3%
3 2
 
3.3%
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 (%)
- 3
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 69
92.0%
Hangul 6
 
8.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 11
15.9%
1 9
13.0%
4 8
11.6%
2 6
8.7%
6 6
8.7%
5 6
8.7%
8 5
7.2%
9 5
7.2%
, 4
 
5.8%
- 3
 
4.3%
Other values (4) 6
8.7%
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 69
92.0%
Hangul 6
 
8.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 11
15.9%
1 9
13.0%
4 8
11.6%
2 6
8.7%
6 6
8.7%
5 6
8.7%
8 5
7.2%
9 5
7.2%
, 4
 
5.8%
- 3
 
4.3%
Other values (4) 6
8.7%
Hangul
ValueCountFrequency (%)
1
16.7%
1
16.7%
1
16.7%
1
16.7%
1
16.7%
1
16.7%

Unnamed: 11
Text

MISSING 

Distinct23
Distinct (%)69.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:53:42.963310image/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 row신안동
2nd row7,481
3rd row12,444
4th row75
5th row1
ValueCountFrequency (%)
0 7
21.2%
1 3
 
9.1%
75 2
 
6.1%
50 2
 
6.1%
7,481 1
 
3.0%
12,444 1
 
3.0%
88 1
 
3.0%
7,454 1
 
3.0%
59 1
 
3.0%
27 1
 
3.0%
Other values (13) 13
39.4%
2024-02-10T09:53:43.793915image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

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

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 11
17.2%
0 10
15.6%
1 9
14.1%
4 9
14.1%
7 5
7.8%
9 5
7.8%
3 4
 
6.2%
2 4
 
6.2%
8 4
 
6.2%
6 3
 
4.7%
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 11
15.7%
0 10
14.3%
1 9
12.9%
4 9
12.9%
7 5
7.1%
9 5
7.1%
3 4
 
5.7%
2 4
 
5.7%
, 4
 
5.7%
8 4
 
5.7%
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 (%)
5 11
15.7%
0 10
14.3%
1 9
12.9%
4 9
12.9%
7 5
7.1%
9 5
7.1%
3 4
 
5.7%
2 4
 
5.7%
, 4
 
5.7%
8 4
 
5.7%
Other values (2) 5
7.1%
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
Minimum2023-08-31 00:00:00
Maximum2023-08-31 00:00:00
2024-02-10T09:53:44.175738image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-10T09:53:44.678551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Unnamed: 13
Text

MISSING 

Distinct27
Distinct (%)81.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:53:45.128904image/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 row18,024
3rd row37,449
4th row81
5th row21
ValueCountFrequency (%)
0 5
 
15.2%
172 2
 
6.1%
1 2
 
6.1%
21 2
 
6.1%
124 1
 
3.0%
181 1
 
3.0%
37,423 1
 
3.0%
18,023 1
 
3.0%
3 1
 
3.0%
26 1
 
3.0%
Other values (16) 16
48.5%
2024-02-10T09:53:46.064647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 19
22.1%
2 12
14.0%
3 11
12.8%
0 8
9.3%
8 7
 
8.1%
7 6
 
7.0%
4 6
 
7.0%
5 4
 
4.7%
, 4
 
4.7%
6 3
 
3.5%
Other values (5) 6
 
7.0%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 19
24.7%
2 12
15.6%
3 11
14.3%
0 8
10.4%
8 7
 
9.1%
7 6
 
7.8%
4 6
 
7.8%
5 4
 
5.2%
6 3
 
3.9%
9 1
 
1.3%
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 83
96.5%
Hangul 3
 
3.5%

Most frequent character per script

Common
ValueCountFrequency (%)
1 19
22.9%
2 12
14.5%
3 11
13.3%
0 8
9.6%
8 7
 
8.4%
7 6
 
7.2%
4 6
 
7.2%
5 4
 
4.8%
, 4
 
4.8%
6 3
 
3.6%
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 19
22.9%
2 12
14.5%
3 11
13.3%
0 8
9.6%
8 7
 
8.4%
7 6
 
7.2%
4 6
 
7.2%
5 4
 
4.8%
, 4
 
4.8%
6 3
 
3.6%
Other values (2) 3
 
3.6%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 14
Text

MISSING 

Distinct24
Distinct (%)72.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:53:46.395044image/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

Unique20 ?
Unique (%)60.6%

Sample

1st row운암1동
2nd row7,383
3rd row18,648
4th row21
5th row22
ValueCountFrequency (%)
0 7
21.2%
22 2
 
6.1%
21 2
 
6.1%
43 2
 
6.1%
61 1
 
3.0%
18,648 1
 
3.0%
104 1
 
3.0%
7,377 1
 
3.0%
14 1
 
3.0%
6 1
 
3.0%
Other values (14) 14
42.4%
2024-02-10T09:53:47.365767image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 11
14.7%
1 11
14.7%
2 9
12.0%
0 8
10.7%
4 8
10.7%
7 6
8.0%
6 5
6.7%
, 4
 
5.3%
8 4
 
5.3%
5 3
 
4.0%
Other values (5) 6
8.0%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 11
16.7%
1 11
16.7%
2 9
13.6%
0 8
12.1%
4 8
12.1%
7 6
9.1%
6 5
7.6%
8 4
 
6.1%
5 3
 
4.5%
9 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 72
96.0%
Hangul 3
 
4.0%

Most frequent character per script

Common
ValueCountFrequency (%)
3 11
15.3%
1 11
15.3%
2 9
12.5%
0 8
11.1%
4 8
11.1%
7 6
8.3%
6 5
6.9%
, 4
 
5.6%
8 4
 
5.6%
5 3
 
4.2%
Other values (2) 3
 
4.2%
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 (%)
3 11
15.3%
1 11
15.3%
2 9
12.5%
0 8
11.1%
4 8
11.1%
7 6
8.3%
6 5
6.9%
, 4
 
5.6%
8 4
 
5.6%
5 3
 
4.2%
Other values (2) 3
 
4.2%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 15
Text

MISSING 

Distinct26
Distinct (%)78.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:53:47.749520image/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

Unique24 ?
Unique (%)72.7%

Sample

1st row운암2동
2nd row5,954
3rd row11,295
4th row56
5th row8
ValueCountFrequency (%)
0 7
21.2%
1 2
 
6.1%
8 2
 
6.1%
51 1
 
3.0%
69 1
 
3.0%
11,314 1
 
3.0%
5,957 1
 
3.0%
19 1
 
3.0%
3 1
 
3.0%
5 1
 
3.0%
Other values (15) 15
45.5%
2024-02-10T09:53:48.572828image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 13
18.1%
1 11
15.3%
0 9
12.5%
4 7
9.7%
9 5
 
6.9%
3 5
 
6.9%
2 4
 
5.6%
, 4
 
5.6%
6 4
 
5.6%
8 3
 
4.2%
Other values (5) 7
9.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 64
88.9%
Other Punctuation 4
 
5.6%
Other Letter 3
 
4.2%
Dash Punctuation 1
 
1.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 13
20.3%
1 11
17.2%
0 9
14.1%
4 7
10.9%
9 5
 
7.8%
3 5
 
7.8%
2 4
 
6.2%
6 4
 
6.2%
8 3
 
4.7%
7 3
 
4.7%
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 69
95.8%
Hangul 3
 
4.2%

Most frequent character per script

Common
ValueCountFrequency (%)
5 13
18.8%
1 11
15.9%
0 9
13.0%
4 7
10.1%
9 5
 
7.2%
3 5
 
7.2%
2 4
 
5.8%
, 4
 
5.8%
6 4
 
5.8%
8 3
 
4.3%
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 (%)
5 13
18.8%
1 11
15.9%
0 9
13.0%
4 7
10.1%
9 5
 
7.2%
3 5
 
7.2%
2 4
 
5.8%
, 4
 
5.8%
6 4
 
5.8%
8 3
 
4.3%
Other values (2) 4
 
5.8%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 16
Text

MISSING 

Distinct24
Distinct (%)72.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:53:48.947574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length2
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

Unique20 ?
Unique (%)60.6%

Sample

1st row운암3동
2nd row5,506
3rd row13,324
4th row33
5th row17
ValueCountFrequency (%)
0 7
21.2%
45 2
 
6.1%
17 2
 
6.1%
1 2
 
6.1%
30 1
 
3.0%
33 1
 
3.0%
93 1
 
3.0%
13,323 1
 
3.0%
5,492 1
 
3.0%
5,506 1
 
3.0%
Other values (14) 14
42.4%
2024-02-10T09:53:49.836058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 14
18.4%
0 11
14.5%
1 11
14.5%
4 7
9.2%
5 7
9.2%
2 5
 
6.6%
6 4
 
5.3%
, 4
 
5.3%
- 3
 
3.9%
9 3
 
3.9%
Other values (5) 7
9.2%

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 (%)
3 14
21.2%
0 11
16.7%
1 11
16.7%
4 7
10.6%
5 7
10.6%
2 5
 
7.6%
6 4
 
6.1%
9 3
 
4.5%
7 2
 
3.0%
8 2
 
3.0%
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 (%)
3 14
19.2%
0 11
15.1%
1 11
15.1%
4 7
9.6%
5 7
9.6%
2 5
 
6.8%
6 4
 
5.5%
, 4
 
5.5%
- 3
 
4.1%
9 3
 
4.1%
Other values (2) 4
 
5.5%
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 (%)
3 14
19.2%
0 11
15.1%
1 11
15.1%
4 7
9.6%
5 7
9.6%
2 5
 
6.8%
6 4
 
5.5%
, 4
 
5.5%
- 3
 
4.1%
9 3
 
4.1%
Other values (2) 4
 
5.5%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 17
Text

MISSING 

Distinct24
Distinct (%)72.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:53:50.166243image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length3
Mean length2.3636364
Min length1

Characters and Unicode

Total characters78
Distinct characters13
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique20 ?
Unique (%)60.6%

Sample

1st row동림동
2nd row10,001
3rd row22,811
4th row31
5th row8
ValueCountFrequency (%)
0 7
21.2%
12 2
 
6.1%
31 2
 
6.1%
85 2
 
6.1%
10,001 1
 
3.0%
8 1
 
3.0%
247 1
 
3.0%
22,896 1
 
3.0%
10,072 1
 
3.0%
71 1
 
3.0%
Other values (14) 14
42.4%
2024-02-10T09:53:51.029202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 17
21.8%
0 12
15.4%
2 10
12.8%
8 8
10.3%
6 6
 
7.7%
5 5
 
6.4%
, 4
 
5.1%
7 4
 
5.1%
3 3
 
3.8%
9 3
 
3.8%
Other values (3) 6
 
7.7%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 17
23.9%
0 12
16.9%
2 10
14.1%
8 8
11.3%
6 6
 
8.5%
5 5
 
7.0%
7 4
 
5.6%
3 3
 
4.2%
9 3
 
4.2%
4 3
 
4.2%
Other Letter
ValueCountFrequency (%)
2
66.7%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
1 17
22.7%
0 12
16.0%
2 10
13.3%
8 8
10.7%
6 6
 
8.0%
5 5
 
6.7%
, 4
 
5.3%
7 4
 
5.3%
3 3
 
4.0%
9 3
 
4.0%
Hangul
ValueCountFrequency (%)
2
66.7%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 17
22.7%
0 12
16.0%
2 10
13.3%
8 8
10.7%
6 6
 
8.0%
5 5
 
6.7%
, 4
 
5.3%
7 4
 
5.3%
3 3
 
4.0%
9 3
 
4.0%
Hangul
ValueCountFrequency (%)
2
66.7%
1
33.3%

Unnamed: 18
Text

MISSING 

Distinct26
Distinct (%)78.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:53:51.479214image/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

Unique24 ?
Unique (%)72.7%

Sample

1st row우산동
2nd row7,609
3rd row15,423
4th row51
5th row8
ValueCountFrequency (%)
0 7
21.2%
8 2
 
6.1%
55 1
 
3.0%
15,454 1
 
3.0%
7,631 1
 
3.0%
1 1
 
3.0%
31 1
 
3.0%
22 1
 
3.0%
18 1
 
3.0%
45 1
 
3.0%
Other values (16) 16
48.5%
2024-02-10T09:53:52.392148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 12
16.4%
0 11
15.1%
1 10
13.7%
4 8
11.0%
2 5
6.8%
3 5
6.8%
8 4
 
5.5%
9 4
 
5.5%
, 4
 
5.5%
7 3
 
4.1%
Other values (5) 7
9.6%

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 (%)
5 12
18.5%
0 11
16.9%
1 10
15.4%
4 8
12.3%
2 5
7.7%
3 5
7.7%
8 4
 
6.2%
9 4
 
6.2%
7 3
 
4.6%
6 3
 
4.6%
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 70
95.9%
Hangul 3
 
4.1%

Most frequent character per script

Common
ValueCountFrequency (%)
5 12
17.1%
0 11
15.7%
1 10
14.3%
4 8
11.4%
2 5
7.1%
3 5
7.1%
8 4
 
5.7%
9 4
 
5.7%
, 4
 
5.7%
7 3
 
4.3%
Other values (2) 4
 
5.7%
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%
0 11
15.7%
1 10
14.3%
4 8
11.4%
2 5
7.1%
3 5
7.1%
8 4
 
5.7%
9 4
 
5.7%
, 4
 
5.7%
7 3
 
4.3%
Other values (2) 4
 
5.7%
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
2024-02-10T09:53:52.725825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
Mean length2
Min length1

Characters and Unicode

Total characters66
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 row풍향동
2nd row2,676
3rd row5,388
4th row23
5th row2
ValueCountFrequency (%)
0 8
24.2%
9 3
 
9.1%
2 2
 
6.1%
36 2
 
6.1%
23 2
 
6.1%
65 1
 
3.0%
29 1
 
3.0%
2,667 1
 
3.0%
3 1
 
3.0%
22 1
 
3.0%
Other values (11) 11
33.3%
2024-02-10T09:53:53.728793image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 11
16.7%
3 9
13.6%
0 8
12.1%
6 8
12.1%
1 6
9.1%
9 5
7.6%
5 5
7.6%
, 4
 
6.1%
7 2
 
3.0%
8 2
 
3.0%
Other values (5) 6
9.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 57
86.4%
Other Punctuation 4
 
6.1%
Other Letter 3
 
4.5%
Dash Punctuation 2
 
3.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 11
19.3%
3 9
15.8%
0 8
14.0%
6 8
14.0%
1 6
10.5%
9 5
8.8%
5 5
8.8%
7 2
 
3.5%
8 2
 
3.5%
4 1
 
1.8%
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 63
95.5%
Hangul 3
 
4.5%

Most frequent character per script

Common
ValueCountFrequency (%)
2 11
17.5%
3 9
14.3%
0 8
12.7%
6 8
12.7%
1 6
9.5%
9 5
7.9%
5 5
7.9%
, 4
 
6.3%
7 2
 
3.2%
8 2
 
3.2%
Other values (2) 3
 
4.8%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 63
95.5%
Hangul 3
 
4.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 11
17.5%
3 9
14.3%
0 8
12.7%
6 8
12.7%
1 6
9.5%
9 5
7.9%
5 5
7.9%
, 4
 
6.3%
7 2
 
3.2%
8 2
 
3.2%
Other values (2) 3
 
4.8%
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
2024-02-10T09:53:54.039759image/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

Unique22 ?
Unique (%)66.7%

Sample

1st row문화동
2nd row9,657
3rd row20,191
4th row36
5th row10
ValueCountFrequency (%)
0 5
 
15.2%
34 2
 
6.1%
1 2
 
6.1%
10 2
 
6.1%
14 1
 
3.0%
165 1
 
3.0%
9,697 1
 
3.0%
2 1
 
3.0%
69 1
 
3.0%
40 1
 
3.0%
Other values (16) 16
48.5%
2024-02-10T09:53:54.868709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 12
15.6%
1 12
15.6%
2 9
11.7%
6 8
10.4%
7 8
10.4%
9 7
9.1%
4 6
7.8%
3 4
 
5.2%
, 4
 
5.2%
5 3
 
3.9%
Other values (4) 4
 
5.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 69
89.6%
Other Punctuation 4
 
5.2%
Other Letter 3
 
3.9%
Dash Punctuation 1
 
1.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 12
17.4%
1 12
17.4%
2 9
13.0%
6 8
11.6%
7 8
11.6%
9 7
10.1%
4 6
8.7%
3 4
 
5.8%
5 3
 
4.3%
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 74
96.1%
Hangul 3
 
3.9%

Most frequent character per script

Common
ValueCountFrequency (%)
0 12
16.2%
1 12
16.2%
2 9
12.2%
6 8
10.8%
7 8
10.8%
9 7
9.5%
4 6
8.1%
3 4
 
5.4%
, 4
 
5.4%
5 3
 
4.1%
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 12
16.2%
1 12
16.2%
2 9
12.2%
6 8
10.8%
7 8
10.8%
9 7
9.5%
4 6
8.1%
3 4
 
5.4%
, 4
 
5.4%
5 3
 
4.1%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 21
Text

MISSING 

Distinct24
Distinct (%)72.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:53:55.209733image/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

Unique21 ?
Unique (%)63.6%

Sample

1st row문흥1동
2nd row6,725
3rd row15,634
4th row19
5th row9
ValueCountFrequency (%)
0 8
24.2%
19 2
 
6.1%
9 2
 
6.1%
40 1
 
3.0%
15,634 1
 
3.0%
53 1
 
3.0%
6,727 1
 
3.0%
1 1
 
3.0%
2 1
 
3.0%
7 1
 
3.0%
Other values (14) 14
42.4%
2024-02-10T09:53:56.164697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 12
16.9%
1 12
16.9%
3 8
11.3%
4 6
8.5%
5 6
8.5%
7 5
7.0%
6 5
7.0%
9 4
 
5.6%
, 4
 
5.6%
2 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 (%)
0 12
19.0%
1 12
19.0%
3 8
12.7%
4 6
9.5%
5 6
9.5%
7 5
7.9%
6 5
7.9%
9 4
 
6.3%
2 3
 
4.8%
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 (%)
- 1
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
0 12
17.6%
1 12
17.6%
3 8
11.8%
4 6
8.8%
5 6
8.8%
7 5
7.4%
6 5
7.4%
9 4
 
5.9%
, 4
 
5.9%
2 3
 
4.4%
Other values (2) 3
 
4.4%
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 12
17.6%
1 12
17.6%
3 8
11.8%
4 6
8.8%
5 6
8.8%
7 5
7.4%
6 5
7.4%
9 4
 
5.9%
, 4
 
5.9%
2 3
 
4.4%
Other values (2) 3
 
4.4%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 22
Text

MISSING 

Distinct23
Distinct (%)69.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:53:56.479927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.1515152
Min length1

Characters and Unicode

Total characters71
Distinct characters14
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique18 ?
Unique (%)54.5%

Sample

1st row문흥2동
2nd row7,361
3rd row15,075
4th row22
5th row6
ValueCountFrequency (%)
0 7
21.2%
6 2
 
6.1%
15,075 2
 
6.1%
22 2
 
6.1%
73 2
 
6.1%
3 1
 
3.0%
140 1
 
3.0%
12 1
 
3.0%
1 1
 
3.0%
2 1
 
3.0%
Other values (13) 13
39.4%
2024-02-10T09:53:57.333164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 12
16.9%
3 10
14.1%
1 8
11.3%
2 8
11.3%
7 7
9.9%
6 7
9.9%
5 5
7.0%
4 5
7.0%
, 4
 
5.6%
9 1
 
1.4%
Other values (4) 4
 
5.6%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 12
18.8%
3 10
15.6%
1 8
12.5%
2 8
12.5%
7 7
10.9%
6 7
10.9%
5 5
7.8%
4 5
7.8%
9 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%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
0 12
17.6%
3 10
14.7%
1 8
11.8%
2 8
11.8%
7 7
10.3%
6 7
10.3%
5 5
7.4%
4 5
7.4%
, 4
 
5.9%
9 1
 
1.5%
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 12
17.6%
3 10
14.7%
1 8
11.8%
2 8
11.8%
7 7
10.3%
6 7
10.3%
5 5
7.4%
4 5
7.4%
, 4
 
5.9%
9 1
 
1.5%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 23
Text

MISSING 

Distinct26
Distinct (%)78.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:53:57.794300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length2
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

Unique23 ?
Unique (%)69.7%

Sample

1st row두암1동
2nd row3,934
3rd row7,342
4th row11
5th row9
ValueCountFrequency (%)
0 6
 
18.2%
1 3
 
9.1%
9 2
 
6.1%
13 1
 
3.0%
11 1
 
3.0%
20 1
 
3.0%
7,366 1
 
3.0%
3,953 1
 
3.0%
24 1
 
3.0%
19 1
 
3.0%
Other values (15) 15
45.5%
2024-02-10T09:53:58.888621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 12
17.4%
2 9
13.0%
0 8
11.6%
3 8
11.6%
9 7
10.1%
4 7
10.1%
5 4
 
5.8%
, 4
 
5.8%
7 3
 
4.3%
6 2
 
2.9%
Other values (5) 5
7.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 61
88.4%
Other Punctuation 4
 
5.8%
Other Letter 3
 
4.3%
Dash Punctuation 1
 
1.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 12
19.7%
2 9
14.8%
0 8
13.1%
3 8
13.1%
9 7
11.5%
4 7
11.5%
5 4
 
6.6%
7 3
 
4.9%
6 2
 
3.3%
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 (%)
- 1
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
1 12
18.2%
2 9
13.6%
0 8
12.1%
3 8
12.1%
9 7
10.6%
4 7
10.6%
5 4
 
6.1%
, 4
 
6.1%
7 3
 
4.5%
6 2
 
3.0%
Other values (2) 2
 
3.0%
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 (%)
1 12
18.2%
2 9
13.6%
0 8
12.1%
3 8
12.1%
9 7
10.6%
4 7
10.6%
5 4
 
6.1%
, 4
 
6.1%
7 3
 
4.5%
6 2
 
3.0%
Other values (2) 2
 
3.0%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 24
Text

MISSING 

Distinct22
Distinct (%)66.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:53:59.394024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.1212121
Min length1

Characters and Unicode

Total characters70
Distinct characters14
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique18 ?
Unique (%)54.5%

Sample

1st row두암2동
2nd row7,603
3rd row15,323
4th row48
5th row9
ValueCountFrequency (%)
0 8
24.2%
9 3
 
9.1%
48 2
 
6.1%
33 2
 
6.1%
47 1
 
3.0%
5 1
 
3.0%
7,609 1
 
3.0%
6 1
 
3.0%
3 1
 
3.0%
49 1
 
3.0%
Other values (12) 12
36.4%
2024-02-10T09:54:00.321945image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 11
15.7%
0 10
14.3%
5 8
11.4%
4 6
8.6%
1 6
8.6%
9 5
7.1%
2 5
7.1%
7 5
7.1%
, 4
 
5.7%
6 4
 
5.7%
Other values (4) 6
8.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 63
90.0%
Other Punctuation 4
 
5.7%
Other Letter 3
 
4.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 11
17.5%
0 10
15.9%
5 8
12.7%
4 6
9.5%
1 6
9.5%
9 5
7.9%
2 5
7.9%
7 5
7.9%
6 4
 
6.3%
8 3
 
4.8%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
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%
5 8
11.9%
4 6
9.0%
1 6
9.0%
9 5
7.5%
2 5
7.5%
7 5
7.5%
, 4
 
6.0%
6 4
 
6.0%
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 11
16.4%
0 10
14.9%
5 8
11.9%
4 6
9.0%
1 6
9.0%
9 5
7.5%
2 5
7.5%
7 5
7.5%
, 4
 
6.0%
6 4
 
6.0%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 25
Text

MISSING 

Distinct24
Distinct (%)72.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:54:00.866612image/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

Unique20 ?
Unique (%)60.6%

Sample

1st row두암3동
2nd row7,628
3rd row12,693
4th row35
5th row8
ValueCountFrequency (%)
1 4
 
12.1%
0 4
 
12.1%
35 3
 
9.1%
8 2
 
6.1%
25 1
 
3.0%
12,693 1
 
3.0%
87 1
 
3.0%
12,669 1
 
3.0%
7,614 1
 
3.0%
2 1
 
3.0%
Other values (14) 14
42.4%
2024-02-10T09:54:01.758579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

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

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 11
17.2%
1 9
14.1%
2 8
12.5%
6 7
10.9%
0 6
9.4%
4 6
9.4%
5 5
7.8%
7 5
7.8%
8 4
 
6.2%
9 3
 
4.7%
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 71
95.9%
Hangul 3
 
4.1%

Most frequent character per script

Common
ValueCountFrequency (%)
3 11
15.5%
1 9
12.7%
2 8
11.3%
6 7
9.9%
0 6
8.5%
4 6
8.5%
5 5
7.0%
7 5
7.0%
8 4
 
5.6%
, 4
 
5.6%
Other values (2) 6
8.5%
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 (%)
3 11
15.5%
1 9
12.7%
2 8
11.3%
6 7
9.9%
0 6
8.5%
4 6
8.5%
5 5
7.0%
7 5
7.0%
8 4
 
5.6%
, 4
 
5.6%
Other values (2) 6
8.5%
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
2024-02-10T09:54:02.224036image/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

Unique20 ?
Unique (%)60.6%

Sample

1st row삼각동
2nd row6,004
3rd row13,490
4th row27
5th row4
ValueCountFrequency (%)
0 7
21.2%
4 2
 
6.1%
27 2
 
6.1%
6 2
 
6.1%
63 1
 
3.0%
13,490 1
 
3.0%
105 1
 
3.0%
6,010 1
 
3.0%
7 1
 
3.0%
6,004 1
 
3.0%
Other values (14) 14
42.4%
2024-02-10T09:54:03.080359image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 14
20.0%
4 9
12.9%
1 8
11.4%
6 7
10.0%
2 6
8.6%
3 6
8.6%
7 4
 
5.7%
5 4
 
5.7%
, 4
 
5.7%
9 3
 
4.3%
Other values (5) 5
 
7.1%

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 (%)
0 14
22.6%
4 9
14.5%
1 8
12.9%
6 7
11.3%
2 6
9.7%
3 6
9.7%
7 4
 
6.5%
5 4
 
6.5%
9 3
 
4.8%
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 (%)
- 1
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
0 14
20.9%
4 9
13.4%
1 8
11.9%
6 7
10.4%
2 6
9.0%
3 6
9.0%
7 4
 
6.0%
5 4
 
6.0%
, 4
 
6.0%
9 3
 
4.5%
Other values (2) 2
 
3.0%
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 (%)
0 14
20.9%
4 9
13.4%
1 8
11.9%
6 7
10.4%
2 6
9.0%
3 6
9.0%
7 4
 
6.0%
5 4
 
6.0%
, 4
 
6.0%
9 3
 
4.5%
Other values (2) 2
 
3.0%
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
2024-02-10T09:54:03.624109image/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

Unique24 ?
Unique (%)72.7%

Sample

1st row일곡동
2nd row11,449
3rd row28,482
4th row25
5th row11
ValueCountFrequency (%)
0 7
21.2%
11 2
 
6.1%
87 1
 
3.0%
28,455 1
 
3.0%
11,450 1
 
3.0%
4 1
 
3.0%
27 1
 
3.0%
1 1
 
3.0%
15 1
 
3.0%
70 1
 
3.0%
Other values (16) 16
48.5%
2024-02-10T09:54:04.439167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 13
17.1%
0 11
14.5%
2 8
10.5%
4 7
9.2%
5 7
9.2%
9 6
7.9%
7 5
 
6.6%
8 5
 
6.6%
6 5
 
6.6%
, 4
 
5.3%
Other values (5) 5
 
6.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 68
89.5%
Other Punctuation 4
 
5.3%
Other Letter 3
 
3.9%
Dash Punctuation 1
 
1.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 13
19.1%
0 11
16.2%
2 8
11.8%
4 7
10.3%
5 7
10.3%
9 6
8.8%
7 5
 
7.4%
8 5
 
7.4%
6 5
 
7.4%
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 (%)
- 1
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
1 13
17.8%
0 11
15.1%
2 8
11.0%
4 7
9.6%
5 7
9.6%
9 6
8.2%
7 5
 
6.8%
8 5
 
6.8%
6 5
 
6.8%
, 4
 
5.5%
Other values (2) 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 (%)
1 13
17.8%
0 11
15.1%
2 8
11.0%
4 7
9.6%
5 7
9.6%
9 6
8.2%
7 5
 
6.8%
8 5
 
6.8%
6 5
 
6.8%
, 4
 
5.5%
Other values (2) 2
 
2.7%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 28
Text

MISSING 

Distinct21
Distinct (%)63.6%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:54:05.066091image/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

Unique18 ?
Unique (%)54.5%

Sample

1st row매곡동
2nd row5,527
3rd row13,448
4th row19
5th row5
ValueCountFrequency (%)
0 8
24.2%
19 5
15.2%
5 2
 
6.1%
3 1
 
3.0%
56 1
 
3.0%
5,513 1
 
3.0%
18 1
 
3.0%
14 1
 
3.0%
7 1
 
3.0%
30 1
 
3.0%
Other values (11) 11
33.3%
2024-02-10T09:54:06.367902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 12
16.7%
1 12
16.7%
5 9
12.5%
4 8
11.1%
9 7
9.7%
3 7
9.7%
, 4
 
5.6%
7 3
 
4.2%
8 3
 
4.2%
- 2
 
2.8%
Other values (5) 5
6.9%

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 (%)
0 12
19.0%
1 12
19.0%
5 9
14.3%
4 8
12.7%
9 7
11.1%
3 7
11.1%
7 3
 
4.8%
8 3
 
4.8%
2 1
 
1.6%
6 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 69
95.8%
Hangul 3
 
4.2%

Most frequent character per script

Common
ValueCountFrequency (%)
0 12
17.4%
1 12
17.4%
5 9
13.0%
4 8
11.6%
9 7
10.1%
3 7
10.1%
, 4
 
5.8%
7 3
 
4.3%
8 3
 
4.3%
- 2
 
2.9%
Other values (2) 2
 
2.9%
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 (%)
0 12
17.4%
1 12
17.4%
5 9
13.0%
4 8
11.6%
9 7
10.1%
3 7
10.1%
, 4
 
5.8%
7 3
 
4.3%
8 3
 
4.3%
- 2
 
2.9%
Other values (2) 2
 
2.9%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 29
Text

MISSING 

Distinct25
Distinct (%)75.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:54:06.761493image/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

Unique23 ?
Unique (%)69.7%

Sample

1st row오치1동
2nd row5,342
3rd row10,245
4th row45
5th row10
ValueCountFrequency (%)
0 8
24.2%
10 2
 
6.1%
62 1
 
3.0%
59 1
 
3.0%
10,249 1
 
3.0%
5,357 1
 
3.0%
2 1
 
3.0%
4 1
 
3.0%
15 1
 
3.0%
5 1
 
3.0%
Other values (15) 15
45.5%
2024-02-10T09:54:08.021734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 14
18.9%
1 11
14.9%
2 9
12.2%
5 9
12.2%
4 8
10.8%
3 5
 
6.8%
, 4
 
5.4%
7 3
 
4.1%
6 3
 
4.1%
8 2
 
2.7%
Other values (5) 6
8.1%

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 14
21.2%
1 11
16.7%
2 9
13.6%
5 9
13.6%
4 8
12.1%
3 5
 
7.6%
7 3
 
4.5%
6 3
 
4.5%
8 2
 
3.0%
9 2
 
3.0%
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 14
19.7%
1 11
15.5%
2 9
12.7%
5 9
12.7%
4 8
11.3%
3 5
 
7.0%
, 4
 
5.6%
7 3
 
4.2%
6 3
 
4.2%
8 2
 
2.8%
Other values (2) 3
 
4.2%
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 14
19.7%
1 11
15.5%
2 9
12.7%
5 9
12.7%
4 8
11.3%
3 5
 
7.0%
, 4
 
5.6%
7 3
 
4.2%
6 3
 
4.2%
8 2
 
2.8%
Other values (2) 3
 
4.2%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 30
Text

MISSING 

Distinct25
Distinct (%)75.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:54:08.558926image/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

Unique22 ?
Unique (%)66.7%

Sample

1st row오치2동
2nd row6,836
3rd row11,801
4th row32
5th row11
ValueCountFrequency (%)
0 7
21.2%
11 2
 
6.1%
32 2
 
6.1%
2 1
 
3.0%
60 1
 
3.0%
11,779 1
 
3.0%
6,815 1
 
3.0%
1 1
 
3.0%
22 1
 
3.0%
21 1
 
3.0%
Other values (15) 15
45.5%
2024-02-10T09:54:09.483295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 19
24.4%
0 11
14.1%
2 9
11.5%
3 7
 
9.0%
6 7
 
9.0%
, 4
 
5.1%
8 4
 
5.1%
5 4
 
5.1%
7 3
 
3.8%
9 3
 
3.8%
Other values (5) 7
 
9.0%

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 19
27.9%
0 11
16.2%
2 9
13.2%
3 7
 
10.3%
6 7
 
10.3%
8 4
 
5.9%
5 4
 
5.9%
7 3
 
4.4%
9 3
 
4.4%
4 1
 
1.5%
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 75
96.2%
Hangul 3
 
3.8%

Most frequent character per script

Common
ValueCountFrequency (%)
1 19
25.3%
0 11
14.7%
2 9
12.0%
3 7
 
9.3%
6 7
 
9.3%
, 4
 
5.3%
8 4
 
5.3%
5 4
 
5.3%
7 3
 
4.0%
9 3
 
4.0%
Other values (2) 4
 
5.3%
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 (%)
1 19
25.3%
0 11
14.7%
2 9
12.0%
3 7
 
9.3%
6 7
 
9.3%
, 4
 
5.3%
8 4
 
5.3%
5 4
 
5.3%
7 3
 
4.0%
9 3
 
4.0%
Other values (2) 4
 
5.3%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 31
Text

MISSING 

Distinct17
Distinct (%)51.5%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:54:10.062804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length1
Mean length1.8484848
Min length1

Characters and Unicode

Total characters61
Distinct characters13
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique10 ?
Unique (%)30.3%

Sample

1st row석곡동
2nd row1,321
3rd row2,354
4th row8
5th row3
ValueCountFrequency (%)
0 9
27.3%
3 5
15.2%
11 2
 
6.1%
9 2
 
6.1%
12 2
 
6.1%
10 2
 
6.1%
8 2
 
6.1%
1 2
 
6.1%
1,321 1
 
3.0%
1,318 1
 
3.0%
Other values (5) 5
15.2%
2024-02-10T09:54:11.172739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 15
24.6%
0 11
18.0%
3 11
18.0%
2 7
11.5%
, 4
 
6.6%
8 3
 
4.9%
9 2
 
3.3%
- 2
 
3.3%
5 2
 
3.3%
1
 
1.6%
Other values (3) 3
 
4.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 52
85.2%
Other Punctuation 4
 
6.6%
Other Letter 3
 
4.9%
Dash Punctuation 2
 
3.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 15
28.8%
0 11
21.2%
3 11
21.2%
2 7
13.5%
8 3
 
5.8%
9 2
 
3.8%
5 2
 
3.8%
4 1
 
1.9%
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 58
95.1%
Hangul 3
 
4.9%

Most frequent character per script

Common
ValueCountFrequency (%)
1 15
25.9%
0 11
19.0%
3 11
19.0%
2 7
12.1%
, 4
 
6.9%
8 3
 
5.2%
9 2
 
3.4%
- 2
 
3.4%
5 2
 
3.4%
4 1
 
1.7%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 58
95.1%
Hangul 3
 
4.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 15
25.9%
0 11
19.0%
3 11
19.0%
2 7
12.1%
, 4
 
6.9%
8 3
 
5.2%
9 2
 
3.4%
- 2
 
3.4%
5 2
 
3.4%
4 1
 
1.7%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 32
Text

MISSING 

Distinct23
Distinct (%)69.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:54:11.517248image/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

Unique20 ?
Unique (%)60.6%

Sample

1st row건국동
2nd row8,931
3rd row21,531
4th row53
5th row7
ValueCountFrequency (%)
0 8
24.2%
53 3
 
9.1%
7 2
 
6.1%
113 1
 
3.0%
21,531 1
 
3.0%
8,931 1
 
3.0%
8,907 1
 
3.0%
83 1
 
3.0%
24 1
 
3.0%
16 1
 
3.0%
Other values (13) 13
39.4%
2024-02-10T09:54:12.494448image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 11
14.5%
0 10
13.2%
3 9
11.8%
2 7
9.2%
4 7
9.2%
8 7
9.2%
5 5
6.6%
7 5
6.6%
9 4
 
5.3%
, 4
 
5.3%
Other values (5) 7
9.2%

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 11
16.4%
0 10
14.9%
3 9
13.4%
2 7
10.4%
4 7
10.4%
8 7
10.4%
5 5
7.5%
7 5
7.5%
9 4
 
6.0%
6 2
 
3.0%
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 73
96.1%
Hangul 3
 
3.9%

Most frequent character per script

Common
ValueCountFrequency (%)
1 11
15.1%
0 10
13.7%
3 9
12.3%
2 7
9.6%
4 7
9.6%
8 7
9.6%
5 5
6.8%
7 5
6.8%
9 4
 
5.5%
, 4
 
5.5%
Other values (2) 4
 
5.5%
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 11
15.1%
0 10
13.7%
3 9
12.3%
2 7
9.6%
4 7
9.6%
8 7
9.6%
5 5
6.8%
7 5
6.8%
9 4
 
5.5%
, 4
 
5.5%
Other values (2) 4
 
5.5%
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
2024-02-10T09:54:12.898946image/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

Unique23 ?
Unique (%)69.7%

Sample

1st row양산동
2nd row16,198
3rd row36,525
4th row74
5th row16
ValueCountFrequency (%)
0 6
 
18.2%
16 2
 
6.1%
74 2
 
6.1%
102 1
 
3.0%
160 1
 
3.0%
36,496 1
 
3.0%
16,211 1
 
3.0%
1 1
 
3.0%
29 1
 
3.0%
13 1
 
3.0%
Other values (16) 16
48.5%
2024-02-10T09:54:13.834895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 20
23.3%
0 9
10.5%
4 9
10.5%
6 8
 
9.3%
3 7
 
8.1%
2 6
 
7.0%
7 5
 
5.8%
9 5
 
5.8%
5 5
 
5.8%
, 4
 
4.7%
Other values (5) 8
 
9.3%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 20
26.0%
0 9
11.7%
4 9
11.7%
6 8
 
10.4%
3 7
 
9.1%
2 6
 
7.8%
7 5
 
6.5%
9 5
 
6.5%
5 5
 
6.5%
8 3
 
3.9%
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 83
96.5%
Hangul 3
 
3.5%

Most frequent character per script

Common
ValueCountFrequency (%)
1 20
24.1%
0 9
10.8%
4 9
10.8%
6 8
 
9.6%
3 7
 
8.4%
2 6
 
7.2%
7 5
 
6.0%
9 5
 
6.0%
5 5
 
6.0%
, 4
 
4.8%
Other values (2) 5
 
6.0%
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 20
24.1%
0 9
10.8%
4 9
10.8%
6 8
 
9.6%
3 7
 
8.4%
2 6
 
7.2%
7 5
 
6.0%
9 5
 
6.0%
5 5
 
6.0%
, 4
 
4.8%
Other values (2) 5
 
6.0%
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
2024-02-10T09:54:14.325227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length3
Mean length2.3636364
Min length1

Characters and Unicode

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

Unique

Unique19 ?
Unique (%)57.6%

Sample

1st row신용동
2nd row11,722
3rd row29,053
4th row12
5th row11
ValueCountFrequency (%)
0 8
24.2%
11,722 2
 
6.1%
12 2
 
6.1%
11 2
 
6.1%
118 1
 
3.0%
29,053 1
 
3.0%
5 1
 
3.0%
6 1
 
3.0%
88 1
 
3.0%
72 1
 
3.0%
Other values (13) 13
39.4%
2024-02-10T09:54:15.297013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 20
25.6%
0 12
15.4%
2 12
15.4%
8 7
 
9.0%
7 5
 
6.4%
, 4
 
5.1%
5 4
 
5.1%
6 4
 
5.1%
9 3
 
3.8%
3 2
 
2.6%
Other values (5) 5
 
6.4%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 20
28.6%
0 12
17.1%
2 12
17.1%
8 7
 
10.0%
7 5
 
7.1%
5 4
 
5.7%
6 4
 
5.7%
9 3
 
4.3%
3 2
 
2.9%
4 1
 
1.4%
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 75
96.2%
Hangul 3
 
3.8%

Most frequent character per script

Common
ValueCountFrequency (%)
1 20
26.7%
0 12
16.0%
2 12
16.0%
8 7
 
9.3%
7 5
 
6.7%
, 4
 
5.3%
5 4
 
5.3%
6 4
 
5.3%
9 3
 
4.0%
3 2
 
2.7%
Other values (2) 2
 
2.7%
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 (%)
1 20
26.7%
0 12
16.0%
2 12
16.0%
8 7
 
9.3%
7 5
 
6.7%
, 4
 
5.3%
5 4
 
5.3%
6 4
 
5.3%
9 3
 
4.0%
3 2
 
2.7%
Other values (2) 2
 
2.7%
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>2023.08.31<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>2023.07 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>198,8062,9104,4253,7092,2734,6177,481<NA>18,0247,3835,9545,50610,0017,6092,6769,6576,7257,3613,9347,6037,6286,00411,4495,5275,3426,8361,3218,93116,19811,722
4<NA>전월말인구수<NA><NA><NA>422,6294,5508,4146,6033,9289,16512,444<NA>37,44918,64811,29513,32422,81115,4235,38820,19115,63415,0757,34215,32312,69313,49028,48213,44810,24511,8012,35421,53136,52529,053
5<NA>전월말거주불명자수<NA><NA><NA>1,020473341342875<NA>8121563331512336192211483527251945328537412
6<NA>전월말재외국민등록자수<NA><NA><NA>238273551<NA>2122817882109699841151011371611
7<NA>증 가 요 인전 입<NA>3,5576610785338199<NA>325104143932471533122710313675122871051658913010723132279210
8<NA><NA><NA>남자<NA>1,834335748204153<NA>1725175451187215106477344674752754976581170144115
9<NA><NA><NA>여자<NA>1,723335037134046<NA>153536848129811612156633155405390405449126213595
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>6010000<NA>2000000101001000000000
26<NA><NA>국외<NA><NA>0000000<NA>0000000000000000000000
27<NA><NA>기타<NA><NA>0000000<NA>0000000000000000000000
28<NA>세대수증감<NA><NA><NA>66819-3-19-16-27<NA>-1-63-147122-940212196-1461-1415-21-3-24130
29<NA>인구수증감<NA><NA><NA>-1541-12-28-16-59<NA>-26-1419-18531-3669-10249-24-7-27-184-22-1-83-29-5
30<NA>거주불명자수증감<NA><NA><NA>-91-2-20-10<NA>30-1-10-10-200-10-2040-2-100-10
31<NA>금월말세대수<NA><NA><NA>198,8722,9184,4443,7062,2544,6017,454<NA>18,0237,3775,9575,49210,0727,6312,6679,6976,7277,3733,9537,6097,6146,01011,4505,5135,3576,8151,3188,90716,21111,722
32<NA>금월말인구수<NA><NA><NA>422,4754,5518,4136,6053,9009,14912,385<NA>37,42318,63411,31413,32322,89615,4545,35220,26015,63315,0757,36615,33212,66913,48328,45513,43010,24911,7792,35321,44836,49629,048
33<NA>금월말거주불명자수<NA><NA><NA>1,011483139342775<NA>8421553231502334192210483327291943318537312
34<NA>금월말재외국민등록자수<NA><NA><NA>238173551<NA>2122817982109699841151011371611

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