Overview

Dataset statistics

Number of variables35
Number of observations35
Missing cells223
Missing cells (%)18.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory9.7 KiB
Average record size in memory284.8 B

Variable types

Unsupported1
Text33
DateTime1

Dataset

Description2022-05-19
Author주민등록인구통계
URLhttps://bigdata.gwangju.go.kr/usr/dataSet/getDataDetailView.rd?dataSetUncd=DS000201927

Alerts

Unnamed: 12 has constant value ""Constant
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 09:41:38.284505
Analysis finished2024-02-10 09:41:39.759638
Duration1.48 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
2024-02-10T09:41:40.033861image/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%
2024-02-10T09:41:41.136041image/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
2024-02-10T09:41:41.561005image/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%
2024-02-10T09:41:42.601538image/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
2024-02-10T09:41:43.010681image/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 row2022.04 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%
2022.04 1
7.1%
현재 1
7.1%
2024-02-10T09:41:43.997007image/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%
0 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%
0 2
33.3%
4 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%
0 2
20.0%
4 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%
0 2
20.0%
4 1
 
10.0%
. 1
 
10.0%

Unnamed: 4
Text

MISSING 

Distinct2
Distinct (%)50.0%
Missing31
Missing (%)88.6%
Memory size412.0 B
2024-02-10T09:41:44.365659image/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%
2024-02-10T09:41:45.380703image/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
2024-02-10T09:41:45.817962image/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

Unique26 ?
Unique (%)78.8%

Sample

1st row합 계
2nd row196,919
3rd row427,178
4th row1,275
5th row220
ValueCountFrequency (%)
0 3
 
8.8%
1 2
 
5.9%
7 2
 
5.9%
1,678 2
 
5.9%
1,291 1
 
2.9%
1,275 1
 
2.9%
220 1
 
2.9%
1,268 1
 
2.9%
426,745 1
 
2.9%
196,995 1
 
2.9%
Other values (19) 19
55.9%
2024-02-10T09:41:47.004066image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 21
16.2%
2 19
14.6%
, 18
13.8%
7 13
10.0%
4 9
6.9%
9 9
6.9%
0 8
 
6.2%
6 8
 
6.2%
3 8
 
6.2%
5 6
 
4.6%
Other values (5) 11
8.5%

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 21
19.8%
2 19
17.9%
7 13
12.3%
4 9
8.5%
9 9
8.5%
0 8
 
7.5%
6 8
 
7.5%
3 8
 
7.5%
5 6
 
5.7%
8 5
 
4.7%
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 21
16.4%
2 19
14.8%
, 18
14.1%
7 13
10.2%
4 9
7.0%
9 9
7.0%
0 8
 
6.2%
6 8
 
6.2%
3 8
 
6.2%
5 6
 
4.7%
Other values (3) 9
7.0%
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 21
16.4%
2 19
14.8%
, 18
14.1%
7 13
10.2%
4 9
7.0%
9 9
7.0%
0 8
 
6.2%
6 8
 
6.2%
3 8
 
6.2%
5 6
 
4.7%
Other values (3) 9
7.0%
Hangul
ValueCountFrequency (%)
1
50.0%
1
50.0%

Unnamed: 6
Text

MISSING 

Distinct24
Distinct (%)72.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:41:47.493875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length2.0909091
Min length1

Characters and Unicode

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

Unique

Unique21 ?
Unique (%)63.6%

Sample

1st row중흥1동
2nd row3,009
3rd row4,772
4th row56
5th row0
ValueCountFrequency (%)
0 8
24.2%
1 2
 
6.1%
18 2
 
6.1%
31 1
 
3.0%
64 1
 
3.0%
4,753 1
 
3.0%
3,006 1
 
3.0%
19 1
 
3.0%
3 1
 
3.0%
6 1
 
3.0%
Other values (14) 14
42.4%
2024-02-10T09:41:48.365907image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 13
18.8%
1 10
14.5%
3 8
11.6%
6 6
8.7%
4 5
 
7.2%
7 5
 
7.2%
, 4
 
5.8%
2 4
 
5.8%
5 4
 
5.8%
9 3
 
4.3%
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 13
21.7%
1 10
16.7%
3 8
13.3%
6 6
10.0%
4 5
 
8.3%
7 5
 
8.3%
2 4
 
6.7%
5 4
 
6.7%
9 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 (%)
- 2
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
0 13
19.7%
1 10
15.2%
3 8
12.1%
6 6
9.1%
4 5
 
7.6%
7 5
 
7.6%
, 4
 
6.1%
2 4
 
6.1%
5 4
 
6.1%
9 3
 
4.5%
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 13
19.7%
1 10
15.2%
3 8
12.1%
6 6
9.1%
4 5
 
7.6%
7 5
 
7.6%
, 4
 
6.1%
2 4
 
6.1%
5 4
 
6.1%
9 3
 
4.5%
Other values (2) 4
 
6.1%
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
2024-02-10T09:41:48.945349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length2.2727273
Min length1

Characters and Unicode

Total characters75
Distinct characters14
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique24 ?
Unique (%)72.7%

Sample

1st row중흥2동
2nd row4,250
3rd row8,111
4th row62
5th row5
ValueCountFrequency (%)
0 7
21.2%
1 2
 
6.1%
113 1
 
3.0%
63 1
 
3.0%
8,323 1
 
3.0%
4,340 1
 
3.0%
212 1
 
3.0%
90 1
 
3.0%
39 1
 
3.0%
33 1
 
3.0%
Other values (16) 16
48.5%
2024-02-10T09:41:50.064363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 13
17.3%
0 12
16.0%
3 10
13.3%
2 8
10.7%
4 8
10.7%
5 5
 
6.7%
, 4
 
5.3%
6 4
 
5.3%
7 4
 
5.3%
8 2
 
2.7%
Other values (4) 5
 
6.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 68
90.7%
Other Punctuation 4
 
5.3%
Other Letter 3
 
4.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 13
19.1%
0 12
17.6%
3 10
14.7%
2 8
11.8%
4 8
11.8%
5 5
 
7.4%
6 4
 
5.9%
7 4
 
5.9%
8 2
 
2.9%
9 2
 
2.9%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
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%
3 10
13.9%
2 8
11.1%
4 8
11.1%
5 5
 
6.9%
, 4
 
5.6%
6 4
 
5.6%
7 4
 
5.6%
8 2
 
2.8%
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%
3 10
13.9%
2 8
11.1%
4 8
11.1%
5 5
 
6.9%
, 4
 
5.6%
6 4
 
5.6%
7 4
 
5.6%
8 2
 
2.8%
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
2024-02-10T09:41:50.430947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length2.2727273
Min length1

Characters and Unicode

Total characters75
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

Unique22 ?
Unique (%)66.7%

Sample

1st row중흥3동
2nd row3,312
3rd row5,952
4th row41
5th row3
ValueCountFrequency (%)
0 6
 
18.2%
1 3
 
9.1%
3 2
 
6.1%
45 1
 
3.0%
41 1
 
3.0%
5,952 1
 
3.0%
6,145 1
 
3.0%
3,370 1
 
3.0%
193 1
 
3.0%
58 1
 
3.0%
Other values (15) 15
45.5%
2024-02-10T09:41:51.516111image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 14
18.7%
0 11
14.7%
3 11
14.7%
6 7
9.3%
4 7
9.3%
5 6
8.0%
2 5
 
6.7%
, 4
 
5.3%
8 3
 
4.0%
7 2
 
2.7%
Other values (4) 5
 
6.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 68
90.7%
Other Punctuation 4
 
5.3%
Other Letter 3
 
4.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 14
20.6%
0 11
16.2%
3 11
16.2%
6 7
10.3%
4 7
10.3%
5 6
8.8%
2 5
 
7.4%
8 3
 
4.4%
7 2
 
2.9%
9 2
 
2.9%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
1 14
19.4%
0 11
15.3%
3 11
15.3%
6 7
9.7%
4 7
9.7%
5 6
8.3%
2 5
 
6.9%
, 4
 
5.6%
8 3
 
4.2%
7 2
 
2.8%
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 14
19.4%
0 11
15.3%
3 11
15.3%
6 7
9.7%
4 7
9.7%
5 6
8.3%
2 5
 
6.9%
, 4
 
5.6%
8 3
 
4.2%
7 2
 
2.8%
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
2024-02-10T09:41:51.923235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
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 row중앙동
2nd row2,235
3rd row3,614
4th row52
5th row4
ValueCountFrequency (%)
0 8
24.2%
4 2
 
6.1%
26 1
 
3.0%
38 1
 
3.0%
3,865 1
 
3.0%
2,337 1
 
3.0%
1 1
 
3.0%
251 1
 
3.0%
102 1
 
3.0%
6 1
 
3.0%
Other values (15) 15
45.5%
2024-02-10T09:41:52.936994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 12
16.2%
1 11
14.9%
0 9
12.2%
3 9
12.2%
5 8
10.8%
6 7
9.5%
4 5
6.8%
, 4
 
5.4%
8 3
 
4.1%
9 1
 
1.4%
Other values (5) 5
6.8%

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 (%)
2 12
18.2%
1 11
16.7%
0 9
13.6%
3 9
13.6%
5 8
12.1%
6 7
10.6%
4 5
7.6%
8 3
 
4.5%
9 1
 
1.5%
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 (%)
- 1
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
2 12
16.9%
1 11
15.5%
0 9
12.7%
3 9
12.7%
5 8
11.3%
6 7
9.9%
4 5
7.0%
, 4
 
5.6%
8 3
 
4.2%
9 1
 
1.4%
Other values (2) 2
 
2.8%
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 (%)
2 12
16.9%
1 11
15.5%
0 9
12.7%
3 9
12.7%
5 8
11.3%
6 7
9.9%
4 5
7.0%
, 4
 
5.6%
8 3
 
4.2%
9 1
 
1.4%
Other values (2) 2
 
2.8%
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
2024-02-10T09:41:53.316087image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.1764706
Min length1

Characters and Unicode

Total characters74
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

Unique22 ?
Unique (%)64.7%

Sample

1st row출력일자 :
2nd row임동
3rd row4,557
4th row9,238
5th row38
ValueCountFrequency (%)
0 8
22.9%
38 2
 
5.7%
9 2
 
5.7%
5 2
 
5.7%
123 1
 
2.9%
6 1
 
2.9%
4,548 1
 
2.9%
48 1
 
2.9%
39 1
 
2.9%
28 1
 
2.9%
Other values (15) 15
42.9%
2024-02-10T09:41:54.159171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 10
13.5%
3 7
9.5%
8 7
9.5%
5 7
9.5%
4 6
8.1%
9 6
8.1%
1 5
 
6.8%
2 5
 
6.8%
6 4
 
5.4%
, 4
 
5.4%
Other values (10) 13
17.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 60
81.1%
Other Letter 6
 
8.1%
Other Punctuation 5
 
6.8%
Dash Punctuation 2
 
2.7%
Space Separator 1
 
1.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 10
16.7%
3 7
11.7%
8 7
11.7%
5 7
11.7%
4 6
10.0%
9 6
10.0%
1 5
8.3%
2 5
8.3%
6 4
 
6.7%
7 3
 
5.0%
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 68
91.9%
Hangul 6
 
8.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 10
14.7%
3 7
10.3%
8 7
10.3%
5 7
10.3%
4 6
8.8%
9 6
8.8%
1 5
7.4%
2 5
7.4%
6 4
 
5.9%
, 4
 
5.9%
Other values (4) 7
10.3%
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 68
91.9%
Hangul 6
 
8.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 10
14.7%
3 7
10.3%
8 7
10.3%
5 7
10.3%
4 6
8.8%
9 6
8.8%
1 5
7.4%
2 5
7.4%
6 4
 
5.9%
, 4
 
5.9%
Other values (4) 7
10.3%
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
2024-02-10T09:41:54.579043image/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

Unique24 ?
Unique (%)72.7%

Sample

1st row신안동
2nd row7,236
3rd row12,395
4th row83
5th row1
ValueCountFrequency (%)
0 7
21.2%
1 2
 
6.1%
103 1
 
3.0%
84 1
 
3.0%
12,346 1
 
3.0%
7,209 1
 
3.0%
49 1
 
3.0%
27 1
 
3.0%
17 1
 
3.0%
64 1
 
3.0%
Other values (16) 16
48.5%
2024-02-10T09:41:55.615503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 12
16.0%
1 10
13.3%
7 7
9.3%
4 7
9.3%
2 6
8.0%
3 6
8.0%
6 6
8.0%
8 5
6.7%
, 4
 
5.3%
9 4
 
5.3%
Other values (5) 8
10.7%

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 (%)
0 12
18.2%
1 10
15.2%
7 7
10.6%
4 7
10.6%
2 6
9.1%
3 6
9.1%
6 6
9.1%
8 5
7.6%
9 4
 
6.1%
5 3
 
4.5%
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 (%)
0 12
16.7%
1 10
13.9%
7 7
9.7%
4 7
9.7%
2 6
8.3%
3 6
8.3%
6 6
8.3%
8 5
6.9%
, 4
 
5.6%
9 4
 
5.6%
Other values (2) 5
6.9%
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 (%)
0 12
16.7%
1 10
13.9%
7 7
9.7%
4 7
9.7%
2 6
8.3%
3 6
8.3%
6 6
8.3%
8 5
6.9%
, 4
 
5.6%
9 4
 
5.6%
Other values (2) 5
6.9%
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
Minimum2022-05-11 00:00:00
Maximum2022-05-11 00:00:00
2024-02-10T09:41:55.919521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-10T09:41:56.478243image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Unnamed: 13
Text

MISSING 

Distinct28
Distinct (%)84.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:41:56.879136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length3
Mean length2.6969697
Min length1

Characters and Unicode

Total characters89
Distinct characters15
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique25 ?
Unique (%)75.8%

Sample

1st row용봉동
2nd row17,894
3rd row38,408
4th row125
5th row18
ValueCountFrequency (%)
0 4
 
12.1%
1 2
 
6.1%
2 2
 
6.1%
125 2
 
6.1%
81 1
 
3.0%
38,408 1
 
3.0%
216 1
 
3.0%
123 1
 
3.0%
38,309 1
 
3.0%
17,887 1
 
3.0%
Other values (17) 17
51.5%
2024-02-10T09:41:57.717601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 17
19.1%
2 10
11.2%
8 10
11.2%
0 8
9.0%
3 8
9.0%
9 8
9.0%
6 6
 
6.7%
5 4
 
4.5%
4 4
 
4.5%
7 4
 
4.5%
Other values (5) 10
11.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 79
88.8%
Other Punctuation 4
 
4.5%
Dash Punctuation 3
 
3.4%
Other Letter 3
 
3.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 17
21.5%
2 10
12.7%
8 10
12.7%
0 8
10.1%
3 8
10.1%
9 8
10.1%
6 6
 
7.6%
5 4
 
5.1%
4 4
 
5.1%
7 4
 
5.1%
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 86
96.6%
Hangul 3
 
3.4%

Most frequent character per script

Common
ValueCountFrequency (%)
1 17
19.8%
2 10
11.6%
8 10
11.6%
0 8
9.3%
3 8
9.3%
9 8
9.3%
6 6
 
7.0%
5 4
 
4.7%
4 4
 
4.7%
7 4
 
4.7%
Other values (2) 7
8.1%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 17
19.8%
2 10
11.6%
8 10
11.6%
0 8
9.3%
3 8
9.3%
9 8
9.3%
6 6
 
7.0%
5 4
 
4.7%
4 4
 
4.7%
7 4
 
4.7%
Other values (2) 7
8.1%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 14
Text

MISSING 

Distinct27
Distinct (%)81.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:41:58.144885image/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 row운암1동
2nd row7,462
3rd row19,265
4th row27
5th row19
ValueCountFrequency (%)
0 6
 
18.2%
54 2
 
6.1%
1 2
 
6.1%
80 1
 
3.0%
26 1
 
3.0%
19,245 1
 
3.0%
7,463 1
 
3.0%
20 1
 
3.0%
2 1
 
3.0%
13 1
 
3.0%
Other values (16) 16
48.5%
2024-02-10T09:41:59.072043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 12
15.8%
0 9
11.8%
7 8
10.5%
2 8
10.5%
4 7
9.2%
6 7
9.2%
5 5
6.6%
9 5
6.6%
, 4
 
5.3%
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 12
17.9%
0 9
13.4%
7 8
11.9%
2 8
11.9%
4 7
10.4%
6 7
10.4%
5 5
7.5%
9 5
7.5%
3 4
 
6.0%
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 (%)
- 2
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
1 12
16.4%
0 9
12.3%
7 8
11.0%
2 8
11.0%
4 7
9.6%
6 7
9.6%
5 5
6.8%
9 5
6.8%
, 4
 
5.5%
3 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 12
16.4%
0 9
12.3%
7 8
11.0%
2 8
11.0%
4 7
9.6%
6 7
9.6%
5 5
6.8%
9 5
6.8%
, 4
 
5.5%
3 4
 
5.5%
Other values (2) 4
 
5.5%
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
2024-02-10T09:41:59.452298image/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

Unique22 ?
Unique (%)66.7%

Sample

1st row운암2동
2nd row6,126
3rd row11,950
4th row55
5th row7
ValueCountFrequency (%)
0 7
21.2%
7 2
 
6.1%
55 2
 
6.1%
2 1
 
3.0%
152 1
 
3.0%
6,117 1
 
3.0%
43 1
 
3.0%
9 1
 
3.0%
13 1
 
3.0%
38 1
 
3.0%
Other values (15) 15
45.5%
2024-02-10T09:42:00.184340image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 13
17.6%
0 9
12.2%
5 9
12.2%
7 7
9.5%
2 7
9.5%
3 7
9.5%
6 6
8.1%
, 4
 
5.4%
9 4
 
5.4%
8 2
 
2.7%
Other values (5) 6
8.1%

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 (%)
1 13
20.0%
0 9
13.8%
5 9
13.8%
7 7
10.8%
2 7
10.8%
3 7
10.8%
6 6
9.2%
9 4
 
6.2%
8 2
 
3.1%
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 (%)
- 2
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
1 13
18.3%
0 9
12.7%
5 9
12.7%
7 7
9.9%
2 7
9.9%
3 7
9.9%
6 6
8.5%
, 4
 
5.6%
9 4
 
5.6%
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 (%)
1 13
18.3%
0 9
12.7%
5 9
12.7%
7 7
9.9%
2 7
9.9%
3 7
9.9%
6 6
8.5%
, 4
 
5.6%
9 4
 
5.6%
8 2
 
2.8%
Other values (2) 3
 
4.2%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 16
Text

MISSING 

Distinct26
Distinct (%)78.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:42:00.571385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length2
Mean length2.3333333
Min length1

Characters and Unicode

Total characters77
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 row운암3동
2nd row5,077
3rd row12,576
4th row30
5th row15
ValueCountFrequency (%)
0 7
21.2%
15 2
 
6.1%
53 1
 
3.0%
12,528 1
 
3.0%
5,059 1
 
3.0%
1 1
 
3.0%
48 1
 
3.0%
18 1
 
3.0%
16 1
 
3.0%
39 1
 
3.0%
Other values (16) 16
48.5%
2024-02-10T09:42:01.544499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 11
14.3%
5 11
14.3%
1 10
13.0%
2 9
11.7%
7 6
7.8%
3 6
7.8%
4 5
6.5%
, 4
 
5.2%
6 3
 
3.9%
9 3
 
3.9%
Other values (5) 9
11.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 67
87.0%
Other Punctuation 4
 
5.2%
Dash Punctuation 3
 
3.9%
Other Letter 3
 
3.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 11
16.4%
5 11
16.4%
1 10
14.9%
2 9
13.4%
7 6
9.0%
3 6
9.0%
4 5
7.5%
6 3
 
4.5%
9 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 (%)
- 3
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
0 11
14.9%
5 11
14.9%
1 10
13.5%
2 9
12.2%
7 6
8.1%
3 6
8.1%
4 5
6.8%
, 4
 
5.4%
6 3
 
4.1%
9 3
 
4.1%
Other values (2) 6
8.1%
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 11
14.9%
5 11
14.9%
1 10
13.5%
2 9
12.2%
7 6
8.1%
3 6
8.1%
4 5
6.8%
, 4
 
5.4%
6 3
 
4.1%
9 3
 
4.1%
Other values (2) 6
8.1%
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
2024-02-10T09:42:01.906389image/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

Unique21 ?
Unique (%)63.6%

Sample

1st row동림동
2nd row9,828
3rd row23,135
4th row55
5th row8
ValueCountFrequency (%)
0 8
24.2%
55 2
 
6.1%
8 2
 
6.1%
64 1
 
3.0%
23,135 1
 
3.0%
118 1
 
3.0%
9,837 1
 
3.0%
47 1
 
3.0%
9 1
 
3.0%
16 1
 
3.0%
Other values (14) 14
42.4%
2024-02-10T09:42:02.678401image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 13
17.1%
8 12
15.8%
1 10
13.2%
5 7
9.2%
7 6
7.9%
9 5
 
6.6%
2 4
 
5.3%
4 4
 
5.3%
, 4
 
5.3%
3 4
 
5.3%
Other values (4) 7
9.2%

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 (%)
0 13
19.1%
8 12
17.6%
1 10
14.7%
5 7
10.3%
7 6
8.8%
9 5
 
7.4%
2 4
 
5.9%
4 4
 
5.9%
3 4
 
5.9%
6 3
 
4.4%
Other Letter
ValueCountFrequency (%)
2
66.7%
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 (%)
0 13
17.8%
8 12
16.4%
1 10
13.7%
5 7
9.6%
7 6
8.2%
9 5
 
6.8%
2 4
 
5.5%
4 4
 
5.5%
, 4
 
5.5%
3 4
 
5.5%
Other values (2) 4
 
5.5%
Hangul
ValueCountFrequency (%)
2
66.7%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 13
17.8%
8 12
16.4%
1 10
13.7%
5 7
9.6%
7 6
8.2%
9 5
 
6.8%
2 4
 
5.5%
4 4
 
5.5%
, 4
 
5.5%
3 4
 
5.5%
Other values (2) 4
 
5.5%
Hangul
ValueCountFrequency (%)
2
66.7%
1
33.3%

Unnamed: 18
Text

MISSING 

Distinct26
Distinct (%)78.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:42:03.051475image/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 row우산동
2nd row5,634
3rd row10,233
4th row63
5th row9
ValueCountFrequency (%)
0 6
 
18.2%
27 2
 
6.1%
9 2
 
6.1%
66 1
 
3.0%
56 1
 
3.0%
10,191 1
 
3.0%
5,624 1
 
3.0%
3 1
 
3.0%
42 1
 
3.0%
10 1
 
3.0%
Other values (16) 16
48.5%
2024-02-10T09:42:03.844081image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 11
14.9%
1 10
13.5%
2 9
12.2%
6 9
12.2%
3 8
10.8%
5 5
6.8%
9 4
 
5.4%
, 4
 
5.4%
4 4
 
5.4%
7 3
 
4.1%
Other values (5) 7
9.5%

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 (%)
0 11
17.2%
1 10
15.6%
2 9
14.1%
6 9
14.1%
3 8
12.5%
5 5
7.8%
9 4
 
6.2%
4 4
 
6.2%
7 3
 
4.7%
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 71
95.9%
Hangul 3
 
4.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 11
15.5%
1 10
14.1%
2 9
12.7%
6 9
12.7%
3 8
11.3%
5 5
7.0%
9 4
 
5.6%
, 4
 
5.6%
4 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%
1 10
14.1%
2 9
12.7%
6 9
12.7%
3 8
11.3%
5 5
7.0%
9 4
 
5.6%
, 4
 
5.6%
4 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: 19
Text

MISSING 

Distinct25
Distinct (%)75.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:42:04.159320image/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

Unique21 ?
Unique (%)63.6%

Sample

1st row풍향동
2nd row2,758
3rd row5,682
4th row24
5th row3
ValueCountFrequency (%)
0 6
18.2%
1 3
 
9.1%
18 2
 
6.1%
3 2
 
6.1%
12 1
 
3.0%
24 1
 
3.0%
22 1
 
3.0%
5,674 1
 
3.0%
2,759 1
 
3.0%
8 1
 
3.0%
Other values (14) 14
42.4%
2024-02-10T09:42:05.198771image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 12
18.2%
0 8
12.1%
1 8
12.1%
5 8
12.1%
8 5
7.6%
3 4
 
6.1%
, 4
 
6.1%
7 4
 
6.1%
9 3
 
4.5%
4 3
 
4.5%
Other values (5) 7
10.6%

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 12
21.1%
0 8
14.0%
1 8
14.0%
5 8
14.0%
8 5
8.8%
3 4
 
7.0%
7 4
 
7.0%
9 3
 
5.3%
4 3
 
5.3%
6 2
 
3.5%
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 63
95.5%
Hangul 3
 
4.5%

Most frequent character per script

Common
ValueCountFrequency (%)
2 12
19.0%
0 8
12.7%
1 8
12.7%
5 8
12.7%
8 5
7.9%
3 4
 
6.3%
, 4
 
6.3%
7 4
 
6.3%
9 3
 
4.8%
4 3
 
4.8%
Other values (2) 4
 
6.3%
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 8
12.7%
1 8
12.7%
5 8
12.7%
8 5
7.9%
3 4
 
6.3%
, 4
 
6.3%
7 4
 
6.3%
9 3
 
4.8%
4 3
 
4.8%
Other values (2) 4
 
6.3%
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
2024-02-10T09:42:05.663030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.3333333
Min length1

Characters and Unicode

Total characters77
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 row문화동
2nd row9,712
3rd row20,727
4th row57
5th row7
ValueCountFrequency (%)
0 7
21.2%
7 2
 
6.1%
88 1
 
3.0%
20,712 1
 
3.0%
9,699 1
 
3.0%
1 1
 
3.0%
15 1
 
3.0%
13 1
 
3.0%
18 1
 
3.0%
48 1
 
3.0%
Other values (16) 16
48.5%
2024-02-10T09:42:06.866356image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 12
15.6%
0 11
14.3%
7 9
11.7%
9 7
9.1%
8 6
7.8%
2 5
6.5%
5 5
6.5%
6 5
6.5%
, 4
 
5.2%
3 4
 
5.2%
Other values (5) 9
11.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 67
87.0%
Other Punctuation 4
 
5.2%
Dash Punctuation 3
 
3.9%
Other Letter 3
 
3.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 12
17.9%
0 11
16.4%
7 9
13.4%
9 7
10.4%
8 6
9.0%
2 5
7.5%
5 5
7.5%
6 5
7.5%
3 4
 
6.0%
4 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 74
96.1%
Hangul 3
 
3.9%

Most frequent character per script

Common
ValueCountFrequency (%)
1 12
16.2%
0 11
14.9%
7 9
12.2%
9 7
9.5%
8 6
8.1%
2 5
6.8%
5 5
6.8%
6 5
6.8%
, 4
 
5.4%
3 4
 
5.4%
Other values (2) 6
8.1%
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 (%)
1 12
16.2%
0 11
14.9%
7 9
12.2%
9 7
9.5%
8 6
8.1%
2 5
6.8%
5 5
6.8%
6 5
6.8%
, 4
 
5.4%
3 4
 
5.4%
Other values (2) 6
8.1%
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
2024-02-10T09:42:07.387346image/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 row문흥1동
2nd row6,481
3rd row15,809
4th row29
5th row9
ValueCountFrequency (%)
0 8
24.2%
9 2
 
6.1%
3 2
 
6.1%
29 2
 
6.1%
126 1
 
3.0%
52 1
 
3.0%
15,809 1
 
3.0%
74 1
 
3.0%
6,478 1
 
3.0%
43 1
 
3.0%
Other values (13) 13
39.4%
2024-02-10T09:42:08.625328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 11
15.1%
9 8
11.0%
1 8
11.0%
6 8
11.0%
4 7
9.6%
3 6
8.2%
7 5
6.8%
2 4
 
5.5%
, 4
 
5.5%
5 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 (%)
0 11
17.2%
9 8
12.5%
1 8
12.5%
6 8
12.5%
4 7
10.9%
3 6
9.4%
7 5
7.8%
2 4
 
6.2%
5 4
 
6.2%
8 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 (%)
0 11
15.7%
9 8
11.4%
1 8
11.4%
6 8
11.4%
4 7
10.0%
3 6
8.6%
7 5
7.1%
2 4
 
5.7%
, 4
 
5.7%
5 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 (%)
0 11
15.7%
9 8
11.4%
1 8
11.4%
6 8
11.4%
4 7
10.0%
3 6
8.6%
7 5
7.1%
2 4
 
5.7%
, 4
 
5.7%
5 4
 
5.7%
Other values (2) 5
7.1%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 22
Text

MISSING 

Distinct25
Distinct (%)75.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:42:09.150964image/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

Unique22 ?
Unique (%)66.7%

Sample

1st row문흥2동
2nd row7,383
3rd row15,594
4th row33
5th row4
ValueCountFrequency (%)
0 6
18.2%
51 3
 
9.1%
4 2
 
6.1%
1 2
 
6.1%
7 1
 
3.0%
183 1
 
3.0%
15,553 1
 
3.0%
7,388 1
 
3.0%
41 1
 
3.0%
5 1
 
3.0%
Other values (14) 14
42.4%
2024-02-10T09:42:10.286738image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 12
16.2%
3 11
14.9%
5 10
13.5%
8 8
10.8%
0 7
9.5%
4 4
 
5.4%
7 4
 
5.4%
, 4
 
5.4%
9 4
 
5.4%
2 4
 
5.4%
Other values (5) 6
8.1%

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 (%)
1 12
18.5%
3 11
16.9%
5 10
15.4%
8 8
12.3%
0 7
10.8%
4 4
 
6.2%
7 4
 
6.2%
9 4
 
6.2%
2 4
 
6.2%
6 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 71
95.9%
Hangul 3
 
4.1%

Most frequent character per script

Common
ValueCountFrequency (%)
1 12
16.9%
3 11
15.5%
5 10
14.1%
8 8
11.3%
0 7
9.9%
4 4
 
5.6%
7 4
 
5.6%
, 4
 
5.6%
9 4
 
5.6%
2 4
 
5.6%
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 (%)
1 12
16.9%
3 11
15.5%
5 10
14.1%
8 8
11.3%
0 7
9.9%
4 4
 
5.6%
7 4
 
5.6%
, 4
 
5.6%
9 4
 
5.6%
2 4
 
5.6%
Other values (2) 3
 
4.2%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 23
Text

MISSING 

Distinct21
Distinct (%)63.6%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:42:10.712753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length2.1212121
Min length1

Characters and Unicode

Total characters70
Distinct characters14
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique16 ?
Unique (%)48.5%

Sample

1st row두암1동
2nd row4,013
3rd row7,736
4th row22
5th row7
ValueCountFrequency (%)
0 8
24.2%
22 3
 
9.1%
7 2
 
6.1%
46 2
 
6.1%
18 2
 
6.1%
87 1
 
3.0%
73 1
 
3.0%
34 1
 
3.0%
39 1
 
3.0%
37 1
 
3.0%
Other values (11) 11
33.3%
2024-02-10T09:42:11.793663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 11
15.7%
1 11
15.7%
7 9
12.9%
2 8
11.4%
4 7
10.0%
3 7
10.0%
, 4
 
5.7%
6 3
 
4.3%
8 3
 
4.3%
- 2
 
2.9%
Other values (4) 5
7.1%

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 (%)
0 11
18.0%
1 11
18.0%
7 9
14.8%
2 8
13.1%
4 7
11.5%
3 7
11.5%
6 3
 
4.9%
8 3
 
4.9%
9 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 67
95.7%
Hangul 3
 
4.3%

Most frequent character per script

Common
ValueCountFrequency (%)
0 11
16.4%
1 11
16.4%
7 9
13.4%
2 8
11.9%
4 7
10.4%
3 7
10.4%
, 4
 
6.0%
6 3
 
4.5%
8 3
 
4.5%
- 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 11
16.4%
1 11
16.4%
7 9
13.4%
2 8
11.9%
4 7
10.4%
3 7
10.4%
, 4
 
6.0%
6 3
 
4.5%
8 3
 
4.5%
- 2
 
3.0%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 24
Text

MISSING 

Distinct24
Distinct (%)72.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:42:12.190352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.1818182
Min length1

Characters and Unicode

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

Unique

Unique21 ?
Unique (%)63.6%

Sample

1st row두암2동
2nd row7,689
3rd row15,934
4th row56
5th row9
ValueCountFrequency (%)
0 7
21.2%
9 3
 
9.1%
56 2
 
6.1%
71 1
 
3.0%
15,934 1
 
3.0%
147 1
 
3.0%
7,698 1
 
3.0%
5 1
 
3.0%
11 1
 
3.0%
53 1
 
3.0%
Other values (14) 14
42.4%
2024-02-10T09:42:13.125532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 8
11.1%
9 8
11.1%
5 8
11.1%
6 8
11.1%
1 7
9.7%
4 7
9.7%
7 7
9.7%
8 4
5.6%
3 4
5.6%
, 4
5.6%
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 (%)
0 8
12.5%
9 8
12.5%
5 8
12.5%
6 8
12.5%
1 7
10.9%
4 7
10.9%
7 7
10.9%
8 4
6.2%
3 4
6.2%
2 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 (%)
0 8
11.6%
9 8
11.6%
5 8
11.6%
6 8
11.6%
1 7
10.1%
4 7
10.1%
7 7
10.1%
8 4
5.8%
3 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 (%)
0 8
11.6%
9 8
11.6%
5 8
11.6%
6 8
11.6%
1 7
10.1%
4 7
10.1%
7 7
10.1%
8 4
5.8%
3 4
5.8%
, 4
5.8%
Other values (2) 4
5.8%
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
2024-02-10T09:42:13.444740image/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 row7,778
3rd row13,248
4th row47
5th row7
ValueCountFrequency (%)
0 7
21.2%
1 2
 
6.1%
47 2
 
6.1%
12 2
 
6.1%
43 2
 
6.1%
7,778 1
 
3.0%
7 1
 
3.0%
89 1
 
3.0%
13,203 1
 
3.0%
7,766 1
 
3.0%
Other values (13) 13
39.4%
2024-02-10T09:42:14.181879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 10
13.5%
3 10
13.5%
4 8
10.8%
1 8
10.8%
7 8
10.8%
2 7
9.5%
8 5
6.8%
6 4
 
5.4%
, 4
 
5.4%
9 3
 
4.1%
Other values (5) 7
9.5%

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 10
15.4%
3 10
15.4%
4 8
12.3%
1 8
12.3%
7 8
12.3%
2 7
10.8%
8 5
7.7%
6 4
 
6.2%
9 3
 
4.6%
5 2
 
3.1%
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 71
95.9%
Hangul 3
 
4.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 10
14.1%
3 10
14.1%
4 8
11.3%
1 8
11.3%
7 8
11.3%
2 7
9.9%
8 5
7.0%
6 4
 
5.6%
, 4
 
5.6%
9 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 10
14.1%
3 10
14.1%
4 8
11.3%
1 8
11.3%
7 8
11.3%
2 7
9.9%
8 5
7.0%
6 4
 
5.6%
, 4
 
5.6%
9 3
 
4.2%
Other values (2) 4
 
5.6%
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
2024-02-10T09:42:14.525103image/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 row6,049
3rd row13,939
4th row31
5th row4
ValueCountFrequency (%)
0 8
24.2%
31 2
 
6.1%
4 2
 
6.1%
86 1
 
3.0%
13,939 1
 
3.0%
88 1
 
3.0%
6,038 1
 
3.0%
58 1
 
3.0%
11 1
 
3.0%
9 1
 
3.0%
Other values (14) 14
42.4%
2024-02-10T09:42:15.315774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

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

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 11
17.2%
1 11
17.2%
3 9
14.1%
8 8
12.5%
6 7
10.9%
9 5
7.8%
4 4
 
6.2%
5 4
 
6.2%
2 3
 
4.7%
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 (%)
- 2
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
0 11
15.7%
1 11
15.7%
3 9
12.9%
8 8
11.4%
6 7
10.0%
9 5
7.1%
4 4
 
5.7%
5 4
 
5.7%
, 4
 
5.7%
2 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 (%)
0 11
15.7%
1 11
15.7%
3 9
12.9%
8 8
11.4%
6 7
10.0%
9 5
7.1%
4 4
 
5.7%
5 4
 
5.7%
, 4
 
5.7%
2 3
 
4.3%
Other values (2) 4
 
5.7%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 27
Text

MISSING 

Distinct27
Distinct (%)81.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:42:15.751319image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length3
Mean length2.4848485
Min length1

Characters and Unicode

Total characters82
Distinct characters15
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique24 ?
Unique (%)72.7%

Sample

1st row일곡동
2nd row11,550
3rd row29,637
4th row33
5th row11
ValueCountFrequency (%)
0 5
 
15.2%
1 3
 
9.1%
11 2
 
6.1%
87 1
 
3.0%
33 1
 
3.0%
29,637 1
 
3.0%
29,549 1
 
3.0%
11,542 1
 
3.0%
88 1
 
3.0%
8 1
 
3.0%
Other values (16) 16
48.5%
2024-02-10T09:42:16.532730image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 20
24.4%
5 9
11.0%
0 7
 
8.5%
2 7
 
8.5%
7 6
 
7.3%
9 5
 
6.1%
8 5
 
6.1%
4 5
 
6.1%
3 5
 
6.1%
, 4
 
4.9%
Other values (5) 9
11.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 72
87.8%
Other Punctuation 4
 
4.9%
Dash Punctuation 3
 
3.7%
Other Letter 3
 
3.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 20
27.8%
5 9
12.5%
0 7
 
9.7%
2 7
 
9.7%
7 6
 
8.3%
9 5
 
6.9%
8 5
 
6.9%
4 5
 
6.9%
3 5
 
6.9%
6 3
 
4.2%
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 79
96.3%
Hangul 3
 
3.7%

Most frequent character per script

Common
ValueCountFrequency (%)
1 20
25.3%
5 9
11.4%
0 7
 
8.9%
2 7
 
8.9%
7 6
 
7.6%
9 5
 
6.3%
8 5
 
6.3%
4 5
 
6.3%
3 5
 
6.3%
, 4
 
5.1%
Other values (2) 6
 
7.6%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 20
25.3%
5 9
11.4%
0 7
 
8.9%
2 7
 
8.9%
7 6
 
7.6%
9 5
 
6.3%
8 5
 
6.3%
4 5
 
6.3%
3 5
 
6.3%
, 4
 
5.1%
Other values (2) 6
 
7.6%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 28
Text

MISSING 

Distinct26
Distinct (%)78.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:42:16.881385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.2424242
Min length1

Characters and Unicode

Total characters74
Distinct characters14
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique24 ?
Unique (%)72.7%

Sample

1st row매곡동
2nd row5,515
3rd row13,766
4th row21
5th row5
ValueCountFrequency (%)
0 7
21.2%
5 2
 
6.1%
76 1
 
3.0%
13,726 1
 
3.0%
5,502 1
 
3.0%
1 1
 
3.0%
40 1
 
3.0%
13 1
 
3.0%
2 1
 
3.0%
47 1
 
3.0%
Other values (16) 16
48.5%
2024-02-10T09:42:17.679250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 12
16.2%
5 11
14.9%
1 10
13.5%
3 6
8.1%
7 6
8.1%
2 6
8.1%
4 5
6.8%
6 5
6.8%
, 4
 
5.4%
9 3
 
4.1%
Other values (4) 6
8.1%

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 (%)
0 12
18.8%
5 11
17.2%
1 10
15.6%
3 6
9.4%
7 6
9.4%
2 6
9.4%
4 5
7.8%
6 5
7.8%
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 (%)
0 12
16.9%
5 11
15.5%
1 10
14.1%
3 6
8.5%
7 6
8.5%
2 6
8.5%
4 5
7.0%
6 5
7.0%
, 4
 
5.6%
9 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 12
16.9%
5 11
15.5%
1 10
14.1%
3 6
8.5%
7 6
8.5%
2 6
8.5%
4 5
7.0%
6 5
7.0%
, 4
 
5.6%
9 3
 
4.2%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 29
Text

MISSING 

Distinct26
Distinct (%)78.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:42:18.015701image/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 row오치1동
2nd row5,525
3rd row10,864
4th row46
5th row8
ValueCountFrequency (%)
0 6
 
18.2%
8 3
 
9.1%
72 1
 
3.0%
10,807 1
 
3.0%
5,506 1
 
3.0%
4 1
 
3.0%
57 1
 
3.0%
19 1
 
3.0%
1 1
 
3.0%
56 1
 
3.0%
Other values (16) 16
48.5%
2024-02-10T09:42:18.788458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 11
15.1%
8 10
13.7%
5 10
13.7%
1 9
12.3%
6 6
8.2%
4 6
8.2%
2 5
6.8%
, 4
 
5.5%
3 3
 
4.1%
7 3
 
4.1%
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 (%)
0 11
17.2%
8 10
15.6%
5 10
15.6%
1 9
14.1%
6 6
9.4%
4 6
9.4%
2 5
7.8%
3 3
 
4.7%
7 3
 
4.7%
9 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 (%)
0 11
15.7%
8 10
14.3%
5 10
14.3%
1 9
12.9%
6 6
8.6%
4 6
8.6%
2 5
7.1%
, 4
 
5.7%
3 3
 
4.3%
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 (%)
0 11
15.7%
8 10
14.3%
5 10
14.3%
1 9
12.9%
6 6
8.6%
4 6
8.6%
2 5
7.1%
, 4
 
5.7%
3 3
 
4.3%
7 3
 
4.3%
Other values (2) 3
 
4.3%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 30
Text

MISSING 

Distinct24
Distinct (%)72.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:42:19.337909image/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 row오치2동
2nd row7,013
3rd row12,462
4th row34
5th row8
ValueCountFrequency (%)
0 7
21.2%
8 2
 
6.1%
34 2
 
6.1%
43 2
 
6.1%
79 1
 
3.0%
12,462 1
 
3.0%
99 1
 
3.0%
6,991 1
 
3.0%
76 1
 
3.0%
22 1
 
3.0%
Other values (14) 14
42.4%
2024-02-10T09:42:20.082727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

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

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 10
15.4%
2 10
15.4%
1 8
12.3%
4 7
10.8%
3 7
10.8%
6 6
9.2%
9 6
9.2%
7 5
7.7%
8 4
 
6.2%
5 2
 
3.1%
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 71
95.9%
Hangul 3
 
4.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 10
14.1%
2 10
14.1%
1 8
11.3%
4 7
9.9%
3 7
9.9%
6 6
8.5%
9 6
8.5%
7 5
7.0%
8 4
 
5.6%
, 4
 
5.6%
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 10
14.1%
2 10
14.1%
1 8
11.3%
4 7
9.9%
3 7
9.9%
6 6
8.5%
9 6
8.5%
7 5
7.0%
8 4
 
5.6%
, 4
 
5.6%
Other values (2) 4
 
5.6%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 31
Text

MISSING 

Distinct18
Distinct (%)54.5%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:42:20.506563image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length1
Mean length1.8181818
Min length1

Characters and Unicode

Total characters60
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

Unique11 ?
Unique (%)33.3%

Sample

1st row석곡동
2nd row1,389
3rd row2,508
4th row21
5th row3
ValueCountFrequency (%)
0 8
24.2%
4 3
 
9.1%
3 3
 
9.1%
5 2
 
6.1%
7 2
 
6.1%
6 2
 
6.1%
21 2
 
6.1%
15 1
 
3.0%
10 1
 
3.0%
석곡동 1
 
3.0%
Other values (8) 8
24.2%
2024-02-10T09:42:21.698521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 12
20.0%
1 10
16.7%
2 7
11.7%
3 5
8.3%
5 5
8.3%
4 4
 
6.7%
, 4
 
6.7%
8 3
 
5.0%
- 2
 
3.3%
7 2
 
3.3%
Other values (5) 6
10.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 51
85.0%
Other Punctuation 4
 
6.7%
Other Letter 3
 
5.0%
Dash Punctuation 2
 
3.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 12
23.5%
1 10
19.6%
2 7
13.7%
3 5
9.8%
5 5
9.8%
4 4
 
7.8%
8 3
 
5.9%
7 2
 
3.9%
6 2
 
3.9%
9 1
 
2.0%
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 57
95.0%
Hangul 3
 
5.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 12
21.1%
1 10
17.5%
2 7
12.3%
3 5
8.8%
5 5
8.8%
4 4
 
7.0%
, 4
 
7.0%
8 3
 
5.3%
- 2
 
3.5%
7 2
 
3.5%
Other values (2) 3
 
5.3%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 57
95.0%
Hangul 3
 
5.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 12
21.1%
1 10
17.5%
2 7
12.3%
3 5
8.8%
5 5
8.8%
4 4
 
7.0%
, 4
 
7.0%
8 3
 
5.3%
- 2
 
3.5%
7 2
 
3.5%
Other values (2) 3
 
5.3%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 32
Text

MISSING 

Distinct27
Distinct (%)81.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:42:22.070852image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.4545455
Min length1

Characters and Unicode

Total characters81
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

Unique25 ?
Unique (%)75.8%

Sample

1st row건국동
2nd row9,216
3rd row22,201
4th row63
5th row12
ValueCountFrequency (%)
0 6
 
18.2%
1 2
 
6.1%
70 2
 
6.1%
12 2
 
6.1%
건국동 1
 
3.0%
131 1
 
3.0%
22,131 1
 
3.0%
9,187 1
 
3.0%
29 1
 
3.0%
18 1
 
3.0%
Other values (15) 15
45.5%
2024-02-10T09:42:23.050806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 18
22.2%
2 13
16.0%
0 11
13.6%
3 6
 
7.4%
7 6
 
7.4%
6 6
 
7.4%
9 4
 
4.9%
, 4
 
4.9%
8 4
 
4.9%
4 3
 
3.7%
Other values (4) 6
 
7.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 71
87.7%
Other Punctuation 4
 
4.9%
Dash Punctuation 3
 
3.7%
Other Letter 3
 
3.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 18
25.4%
2 13
18.3%
0 11
15.5%
3 6
 
8.5%
7 6
 
8.5%
6 6
 
8.5%
9 4
 
5.6%
8 4
 
5.6%
4 3
 
4.2%
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 78
96.3%
Hangul 3
 
3.7%

Most frequent character per script

Common
ValueCountFrequency (%)
1 18
23.1%
2 13
16.7%
0 11
14.1%
3 6
 
7.7%
7 6
 
7.7%
6 6
 
7.7%
9 4
 
5.1%
, 4
 
5.1%
8 4
 
5.1%
4 3
 
3.8%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 78
96.3%
Hangul 3
 
3.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 18
23.1%
2 13
16.7%
0 11
14.1%
3 6
 
7.7%
7 6
 
7.7%
6 6
 
7.7%
9 4
 
5.1%
, 4
 
5.1%
8 4
 
5.1%
4 3
 
3.8%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 33
Text

MISSING 

Distinct24
Distinct (%)72.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:42:23.451516image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length3
Mean length2.5757576
Min length1

Characters and Unicode

Total characters85
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 row양산동
2nd row16,405
3rd row37,705
4th row63
5th row19
ValueCountFrequency (%)
0 8
24.2%
63 2
 
6.1%
19 2
 
6.1%
89 1
 
3.0%
37,705 1
 
3.0%
176 1
 
3.0%
16,419 1
 
3.0%
57 1
 
3.0%
14 1
 
3.0%
13 1
 
3.0%
Other values (14) 14
42.4%
2024-02-10T09:42:24.399025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 16
18.8%
0 12
14.1%
6 8
9.4%
8 8
9.4%
3 7
8.2%
4 6
 
7.1%
7 6
 
7.1%
9 5
 
5.9%
5 5
 
5.9%
2 4
 
4.7%
Other values (5) 8
9.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 77
90.6%
Other Punctuation 4
 
4.7%
Other Letter 3
 
3.5%
Dash Punctuation 1
 
1.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 16
20.8%
0 12
15.6%
6 8
10.4%
8 8
10.4%
3 7
9.1%
4 6
 
7.8%
7 6
 
7.8%
9 5
 
6.5%
5 5
 
6.5%
2 4
 
5.2%
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 82
96.5%
Hangul 3
 
3.5%

Most frequent character per script

Common
ValueCountFrequency (%)
1 16
19.5%
0 12
14.6%
6 8
9.8%
8 8
9.8%
3 7
8.5%
4 6
 
7.3%
7 6
 
7.3%
9 5
 
6.1%
5 5
 
6.1%
2 4
 
4.9%
Other values (2) 5
 
6.1%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 82
96.5%
Hangul 3
 
3.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 16
19.5%
0 12
14.6%
6 8
9.8%
8 8
9.8%
3 7
8.5%
4 6
 
7.3%
7 6
 
7.3%
9 5
 
6.1%
5 5
 
6.1%
2 4
 
4.9%
Other values (2) 5
 
6.1%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 34
Text

MISSING 

Distinct24
Distinct (%)72.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:42:24.780135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length3
Mean length2.4242424
Min length1

Characters and Unicode

Total characters80
Distinct characters14
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique21 ?
Unique (%)63.6%

Sample

1st row신용동
2nd row11,823
3rd row29,717
4th row8
5th row10
ValueCountFrequency (%)
0 7
21.2%
10 3
 
9.1%
8 2
 
6.1%
92 1
 
3.0%
29,717 1
 
3.0%
142 1
 
3.0%
29,677 1
 
3.0%
11,833 1
 
3.0%
1 1
 
3.0%
40 1
 
3.0%
Other values (14) 14
42.4%
2024-02-10T09:42:25.772304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 16
20.0%
0 15
18.8%
2 10
12.5%
8 8
10.0%
7 8
10.0%
9 5
 
6.2%
, 4
 
5.0%
6 3
 
3.8%
4 3
 
3.8%
3 3
 
3.8%
Other values (4) 5
 
6.2%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 16
22.5%
0 15
21.1%
2 10
14.1%
8 8
11.3%
7 8
11.3%
9 5
 
7.0%
6 3
 
4.2%
4 3
 
4.2%
3 3
 
4.2%
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 77
96.2%
Hangul 3
 
3.8%

Most frequent character per script

Common
ValueCountFrequency (%)
1 16
20.8%
0 15
19.5%
2 10
13.0%
8 8
10.4%
7 8
10.4%
9 5
 
6.5%
, 4
 
5.2%
6 3
 
3.9%
4 3
 
3.9%
3 3
 
3.9%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 16
20.8%
0 15
19.5%
2 10
13.0%
8 8
10.4%
7 8
10.4%
9 5
 
6.5%
, 4
 
5.2%
6 3
 
3.9%
4 3
 
3.9%
3 3
 
3.9%
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>2022.05.11<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>2022.04 현재<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><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>196,9193,0094,2503,3122,2354,5577,236<NA>17,8947,4626,1265,0779,8285,6342,7589,7126,4817,3834,0137,6897,7786,04911,5505,5155,5257,0131,3899,21616,40511,823
4<NA>전월말인구수<NA><NA><NA>427,1784,7728,1115,9523,6149,23812,395<NA>38,40819,26511,95012,57623,13510,2335,68220,72715,80915,5947,73615,93413,24813,93929,63713,76610,86412,4622,50822,20137,70529,717
5<NA>전월말거주불명자수<NA><NA><NA>1,275566241523883<NA>12527553055632457293322564731332146342163638
6<NA>전월말재외국민등록자수<NA><NA><NA>220053451<NA>18197158937947974115883121910
7<NA>증 가 요 인전 입<NA>4,2014632431032178141<NA>346147119711788345171961527314589115175104889915173281216
8<NA><NA><NA>남자<NA>2,125261701481594381<NA>180706835783725100496934674066975343431082146106
9<NA><NA><NA>여자<NA>2,076201541621623560<NA>16677513610046207147833978494978514556591135110
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>7000000<NA>0200010000001010100100
26<NA><NA>국외<NA><NA>0000000<NA>0000000000000000000000
27<NA><NA>기타<NA><NA>1000000<NA>1000000000000000000000
28<NA>세대수증감<NA><NA><NA>76-39058102-9-27<NA>-71-9-189-101-13-35-39-12-11-8-13-19-22-7-291410
29<NA>인구수증감<NA><NA><NA>-433-19212193251-48-49<NA>-99-20-43-48-47-42-8-15-43-41-24-5-45-58-88-40-57-76-7-70-57-40
30<NA>거주불명자수증감<NA><NA><NA>-7111-101<NA>-2-10-10-3-1-10-10000-1-1400-10-1
31<NA>금월말세대수<NA><NA><NA>196,9953,0064,3403,3702,3374,5487,209<NA>17,8877,4636,1175,0599,8375,6242,7599,6996,4787,3884,0107,6987,7666,03811,5425,5025,5066,9911,3829,18716,41911,833
32<NA>금월말인구수<NA><NA><NA>426,7454,7538,3236,1453,8659,19012,346<NA>38,30919,24511,90712,52823,08810,1915,67420,71215,76615,5537,71215,92913,20313,88129,54913,72610,80712,3862,50122,13137,64829,677
33<NA>금월말거주불명자수<NA><NA><NA>1,268576342513884<NA>12326552955602356293222564731322050342162637
34<NA>금월말재외국민등록자수<NA><NA><NA>222063452<NA>19177158937947984115883121910