Overview

Dataset statistics

Number of variables35
Number of observations35
Missing cells223
Missing cells (%)18.2%
Duplicate rows2
Duplicate rows (%)5.7%
Total size in memory9.7 KiB
Average record size in memory284.8 B

Variable types

Unsupported1
Text33
DateTime1

Dataset

Description2022-04-15
Author주민등록인구통계
URLhttps://bigdata.gwangju.go.kr/usr/dataSet/getDataDetailView.rd?dataSetUncd=DS000201927

Alerts

Unnamed: 12 has constant value ""Constant
Dataset has 2 (5.7%) duplicate rowsDuplicates
Unnamed: 0 has 35 (100.0%) missing valuesMissing
인구이동보고서(1호) has 19 (54.3%) missing valuesMissing
Unnamed: 2 has 24 (68.6%) missing valuesMissing
Unnamed: 3 has 23 (65.7%) missing valuesMissing
Unnamed: 4 has 31 (88.6%) missing valuesMissing
Unnamed: 5 has 2 (5.7%) missing valuesMissing
Unnamed: 6 has 2 (5.7%) missing valuesMissing
Unnamed: 7 has 2 (5.7%) missing valuesMissing
Unnamed: 8 has 2 (5.7%) missing valuesMissing
Unnamed: 9 has 2 (5.7%) missing valuesMissing
Unnamed: 10 has 1 (2.9%) missing valuesMissing
Unnamed: 11 has 2 (5.7%) missing valuesMissing
Unnamed: 12 has 34 (97.1%) missing valuesMissing
Unnamed: 13 has 2 (5.7%) missing valuesMissing
Unnamed: 14 has 2 (5.7%) missing valuesMissing
Unnamed: 15 has 2 (5.7%) missing valuesMissing
Unnamed: 16 has 2 (5.7%) missing valuesMissing
Unnamed: 17 has 2 (5.7%) missing valuesMissing
Unnamed: 18 has 2 (5.7%) missing valuesMissing
Unnamed: 19 has 2 (5.7%) missing valuesMissing
Unnamed: 20 has 2 (5.7%) missing valuesMissing
Unnamed: 21 has 2 (5.7%) missing valuesMissing
Unnamed: 22 has 2 (5.7%) missing valuesMissing
Unnamed: 23 has 2 (5.7%) missing valuesMissing
Unnamed: 24 has 2 (5.7%) missing valuesMissing
Unnamed: 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 09:40:42.208075
Analysis finished2024-02-10 09:40:44.262404
Duration2.05 seconds
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
2024-02-10T09:40:44.506529image/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%
2024-02-10T09:40:45.674411image/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
2024-02-10T09:40:46.105657image/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%
2024-02-10T09:40:47.126695image/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
2024-02-10T09:40:47.520660image/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 row2022.03 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%
2022.03 1
7.1%
현재 1
7.1%
2024-02-10T09:40:48.486238image/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%
3 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%
3 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%
3 1
 
10.0%
. 1
 
10.0%

Unnamed: 4
Text

MISSING 

Distinct2
Distinct (%)50.0%
Missing31
Missing (%)88.6%
Memory size412.0 B
2024-02-10T09:40:48.840510image/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%
2024-02-10T09:40:49.871984image/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
2024-02-10T09:40:50.345162image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length3.8787879
Min length1

Characters and Unicode

Total characters128
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 row196,446
3rd row427,139
4th row1,280
5th row219
ValueCountFrequency (%)
0 5
 
14.7%
2,502 2
 
5.9%
2,929 1
 
2.9%
3,144 1
 
2.9%
1,275 1
 
2.9%
427,178 1
 
2.9%
196,919 1
 
2.9%
5 1
 
2.9%
39 1
 
2.9%
473 1
 
2.9%
Other values (19) 19
55.9%
2024-02-10T09:40:51.300286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 21
16.4%
, 18
14.1%
1 17
13.3%
0 12
9.4%
9 11
8.6%
3 10
7.8%
5 8
 
6.2%
7 8
 
6.2%
4 8
 
6.2%
6 7
 
5.5%
Other values (5) 8
 
6.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 105
82.0%
Other Punctuation 18
 
14.1%
Space Separator 2
 
1.6%
Other Letter 2
 
1.6%
Dash Punctuation 1
 
0.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 21
20.0%
1 17
16.2%
0 12
11.4%
9 11
10.5%
3 10
9.5%
5 8
 
7.6%
7 8
 
7.6%
4 8
 
7.6%
6 7
 
6.7%
8 3
 
2.9%
Other Letter
ValueCountFrequency (%)
1
50.0%
1
50.0%
Other Punctuation
ValueCountFrequency (%)
, 18
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 126
98.4%
Hangul 2
 
1.6%

Most frequent character per script

Common
ValueCountFrequency (%)
2 21
16.7%
, 18
14.3%
1 17
13.5%
0 12
9.5%
9 11
8.7%
3 10
7.9%
5 8
 
6.3%
7 8
 
6.3%
4 8
 
6.3%
6 7
 
5.6%
Other values (3) 6
 
4.8%
Hangul
ValueCountFrequency (%)
1
50.0%
1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 126
98.4%
Hangul 2
 
1.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 21
16.7%
, 18
14.3%
1 17
13.5%
0 12
9.5%
9 11
8.7%
3 10
7.9%
5 8
 
6.3%
7 8
 
6.3%
4 8
 
6.3%
6 7
 
5.6%
Other values (3) 6
 
4.8%
Hangul
ValueCountFrequency (%)
1
50.0%
1
50.0%

Unnamed: 6
Text

MISSING 

Distinct25
Distinct (%)75.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:40:51.635348image/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

Unique24 ?
Unique (%)72.7%

Sample

1st row중흥1동
2nd row3,007
3rd row4,791
4th row58
5th row0
ValueCountFrequency (%)
0 9
27.3%
2 2
 
6.1%
3,007 1
 
3.0%
45 1
 
3.0%
4,772 1
 
3.0%
3,009 1
 
3.0%
19 1
 
3.0%
3 1
 
3.0%
22 1
 
3.0%
25 1
 
3.0%
Other values (14) 14
42.4%
2024-02-10T09:40:52.509702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 15
21.7%
2 9
13.0%
5 6
 
8.7%
3 5
 
7.2%
4 5
 
7.2%
9 5
 
7.2%
, 4
 
5.8%
7 4
 
5.8%
1 4
 
5.8%
6 4
 
5.8%
Other values (5) 8
11.6%

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 15
25.0%
2 9
15.0%
5 6
 
10.0%
3 5
 
8.3%
4 5
 
8.3%
9 5
 
8.3%
7 4
 
6.7%
1 4
 
6.7%
6 4
 
6.7%
8 3
 
5.0%
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 66
95.7%
Hangul 3
 
4.3%

Most frequent character per script

Common
ValueCountFrequency (%)
0 15
22.7%
2 9
13.6%
5 6
 
9.1%
3 5
 
7.6%
4 5
 
7.6%
9 5
 
7.6%
, 4
 
6.1%
7 4
 
6.1%
1 4
 
6.1%
6 4
 
6.1%
Other values (2) 5
 
7.6%
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 15
22.7%
2 9
13.6%
5 6
 
9.1%
3 5
 
7.6%
4 5
 
7.6%
9 5
 
7.6%
, 4
 
6.1%
7 4
 
6.1%
1 4
 
6.1%
6 4
 
6.1%
Other values (2) 5
 
7.6%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 7
Text

MISSING 

Distinct25
Distinct (%)75.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:40:52.894057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
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

Unique22 ?
Unique (%)66.7%

Sample

1st row중흥2동
2nd row4,042
3rd row7,569
4th row63
5th row4
ValueCountFrequency (%)
0 7
21.2%
84 2
 
6.1%
4 2
 
6.1%
150 1
 
3.0%
70 1
 
3.0%
62 1
 
3.0%
8,111 1
 
3.0%
4,250 1
 
3.0%
1 1
 
3.0%
542 1
 
3.0%
Other values (15) 15
45.5%
2024-02-10T09:40:53.776051image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 12
15.6%
4 9
11.7%
2 8
10.4%
5 8
10.4%
6 7
9.1%
3 7
9.1%
1 6
7.8%
8 5
6.5%
, 4
 
5.2%
7 4
 
5.2%
Other values (5) 7
9.1%

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%
4 9
13.0%
2 8
11.6%
5 8
11.6%
6 7
10.1%
3 7
10.1%
1 6
8.7%
8 5
7.2%
7 4
 
5.8%
9 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%
4 9
12.2%
2 8
10.8%
5 8
10.8%
6 7
9.5%
3 7
9.5%
1 6
8.1%
8 5
6.8%
, 4
 
5.4%
7 4
 
5.4%
Other values (2) 4
 
5.4%
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%
4 9
12.2%
2 8
10.8%
5 8
10.8%
6 7
9.5%
3 7
9.5%
1 6
8.1%
8 5
6.8%
, 4
 
5.4%
7 4
 
5.4%
Other values (2) 4
 
5.4%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 8
Text

MISSING 

Distinct23
Distinct (%)69.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:40:54.270264image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length2.3030303
Min length1

Characters and Unicode

Total characters76
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

Unique19 ?
Unique (%)57.6%

Sample

1st row중흥3동
2nd row3,133
3rd row5,508
4th row41
5th row3
ValueCountFrequency (%)
0 8
24.2%
3 2
 
6.1%
41 2
 
6.1%
4 2
 
6.1%
80 1
 
3.0%
5,508 1
 
3.0%
81 1
 
3.0%
3,312 1
 
3.0%
444 1
 
3.0%
179 1
 
3.0%
Other values (13) 13
39.4%
2024-02-10T09:40:55.225579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 11
14.5%
3 11
14.5%
4 10
13.2%
1 9
11.8%
5 7
9.2%
2 7
9.2%
9 5
6.6%
, 4
 
5.3%
8 4
 
5.3%
6 3
 
3.9%
Other values (4) 5
6.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 69
90.8%
Other Punctuation 4
 
5.3%
Other Letter 3
 
3.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 11
15.9%
3 11
15.9%
4 10
14.5%
1 9
13.0%
5 7
10.1%
2 7
10.1%
9 5
7.2%
8 4
 
5.8%
6 3
 
4.3%
7 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 73
96.1%
Hangul 3
 
3.9%

Most frequent character per script

Common
ValueCountFrequency (%)
0 11
15.1%
3 11
15.1%
4 10
13.7%
1 9
12.3%
5 7
9.6%
2 7
9.6%
9 5
6.8%
, 4
 
5.5%
8 4
 
5.5%
6 3
 
4.1%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 11
15.1%
3 11
15.1%
4 10
13.7%
1 9
12.3%
5 7
9.6%
2 7
9.6%
9 5
6.8%
, 4
 
5.5%
8 4
 
5.5%
6 3
 
4.1%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 9
Text

MISSING 

Distinct25
Distinct (%)75.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:40:55.537920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
Mean length2.2727273
Min length1

Characters and Unicode

Total characters75
Distinct characters15
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique22 ?
Unique (%)66.7%

Sample

1st row중앙동
2nd row2,015
3rd row3,055
4th row53
5th row4
ValueCountFrequency (%)
0 6
18.2%
1 3
 
9.1%
4 3
 
9.1%
21 1
 
3.0%
53 1
 
3.0%
3,055 1
 
3.0%
3,614 1
 
3.0%
2,235 1
 
3.0%
559 1
 
3.0%
220 1
 
3.0%
Other values (14) 14
42.4%
2024-02-10T09:40:56.395434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 14
18.7%
0 10
13.3%
1 10
13.3%
5 10
13.3%
2 9
12.0%
4 6
8.0%
, 4
 
5.3%
9 3
 
4.0%
6 2
 
2.7%
7 2
 
2.7%
Other values (5) 5
 
6.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 67
89.3%
Other Punctuation 4
 
5.3%
Other Letter 3
 
4.0%
Dash Punctuation 1
 
1.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 14
20.9%
0 10
14.9%
1 10
14.9%
5 10
14.9%
2 9
13.4%
4 6
9.0%
9 3
 
4.5%
6 2
 
3.0%
7 2
 
3.0%
8 1
 
1.5%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
3 14
19.4%
0 10
13.9%
1 10
13.9%
5 10
13.9%
2 9
12.5%
4 6
8.3%
, 4
 
5.6%
9 3
 
4.2%
6 2
 
2.8%
7 2
 
2.8%
Other values (2) 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 (%)
3 14
19.4%
0 10
13.9%
1 10
13.9%
5 10
13.9%
2 9
12.5%
4 6
8.3%
, 4
 
5.6%
9 3
 
4.2%
6 2
 
2.8%
7 2
 
2.8%
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
2024-02-10T09:40:56.913575image/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

Unique21 ?
Unique (%)61.8%

Sample

1st row출력일자 :
2nd row임동
3rd row4,564
4th row9,265
5th row37
ValueCountFrequency (%)
0 6
 
17.1%
5 3
 
8.6%
62 2
 
5.7%
1 2
 
5.7%
7 2
 
5.7%
출력일자 1
 
2.9%
9,238 1
 
2.9%
4,557 1
 
2.9%
27 1
 
2.9%
36 1
 
2.9%
Other values (15) 15
42.9%
2024-02-10T09:40:57.815640image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 13
17.3%
7 8
10.7%
0 7
9.3%
2 7
9.3%
6 6
8.0%
1 5
 
6.7%
4 5
 
6.7%
, 4
 
5.3%
3 4
 
5.3%
9 3
 
4.0%
Other values (10) 13
17.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 61
81.3%
Other Letter 6
 
8.0%
Other Punctuation 5
 
6.7%
Dash Punctuation 2
 
2.7%
Space Separator 1
 
1.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 13
21.3%
7 8
13.1%
0 7
11.5%
2 7
11.5%
6 6
9.8%
1 5
 
8.2%
4 5
 
8.2%
3 4
 
6.6%
9 3
 
4.9%
8 3
 
4.9%
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 69
92.0%
Hangul 6
 
8.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 13
18.8%
7 8
11.6%
0 7
10.1%
2 7
10.1%
6 6
8.7%
1 5
 
7.2%
4 5
 
7.2%
, 4
 
5.8%
3 4
 
5.8%
9 3
 
4.3%
Other values (4) 7
10.1%
Hangul
ValueCountFrequency (%)
1
16.7%
1
16.7%
1
16.7%
1
16.7%
1
16.7%
1
16.7%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 13
18.8%
7 8
11.6%
0 7
10.1%
2 7
10.1%
6 6
8.7%
1 5
 
7.2%
4 5
 
7.2%
, 4
 
5.8%
3 4
 
5.8%
9 3
 
4.3%
Other values (4) 7
10.1%
Hangul
ValueCountFrequency (%)
1
16.7%
1
16.7%
1
16.7%
1
16.7%
1
16.7%
1
16.7%

Unnamed: 11
Text

MISSING 

Distinct25
Distinct (%)75.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:40:58.132486image/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

Unique22 ?
Unique (%)66.7%

Sample

1st row신안동
2nd row7,216
3rd row12,361
4th row84
5th row1
ValueCountFrequency (%)
0 7
21.2%
1 3
 
9.1%
86 2
 
6.1%
72 1
 
3.0%
91 1
 
3.0%
12,395 1
 
3.0%
7,236 1
 
3.0%
34 1
 
3.0%
20 1
 
3.0%
9 1
 
3.0%
Other values (14) 14
42.4%
2024-02-10T09:40:59.060539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 14
18.4%
2 13
17.1%
0 9
11.8%
6 7
9.2%
3 7
9.2%
7 5
 
6.6%
8 4
 
5.3%
, 4
 
5.3%
4 4
 
5.3%
9 3
 
3.9%
Other values (5) 6
7.9%

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 14
20.6%
2 13
19.1%
0 9
13.2%
6 7
10.3%
3 7
10.3%
7 5
 
7.4%
8 4
 
5.9%
4 4
 
5.9%
9 3
 
4.4%
5 2
 
2.9%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
1 14
19.2%
2 13
17.8%
0 9
12.3%
6 7
9.6%
3 7
9.6%
7 5
 
6.8%
8 4
 
5.5%
, 4
 
5.5%
4 4
 
5.5%
9 3
 
4.1%
Other values (2) 3
 
4.1%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 14
19.2%
2 13
17.8%
0 9
12.3%
6 7
9.6%
3 7
9.6%
7 5
 
6.8%
8 4
 
5.5%
, 4
 
5.5%
4 4
 
5.5%
9 3
 
4.1%
Other values (2) 3
 
4.1%
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
Minimum2022-04-12 00:00:00
Maximum2022-04-12 00:00:00
2024-02-10T09:40:59.496774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-10T09:40:59.944865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Unnamed: 13
Text

MISSING 

Distinct24
Distinct (%)72.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:41:00.377908image/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

Unique21 ?
Unique (%)63.6%

Sample

1st row용봉동
2nd row17,853
3rd row38,475
4th row125
5th row18
ValueCountFrequency (%)
0 8
24.2%
125 2
 
6.1%
18 2
 
6.1%
217 1
 
3.0%
38,475 1
 
3.0%
330 1
 
3.0%
17,894 1
 
3.0%
67 1
 
3.0%
41 1
 
3.0%
23 1
 
3.0%
Other values (14) 14
42.4%
2024-02-10T09:41:01.254849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 17
19.1%
8 12
13.5%
2 11
12.4%
0 10
11.2%
7 7
7.9%
5 6
 
6.7%
3 6
 
6.7%
4 5
 
5.6%
6 4
 
4.5%
, 4
 
4.5%
Other values (5) 7
7.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 81
91.0%
Other Punctuation 4
 
4.5%
Other Letter 3
 
3.4%
Dash Punctuation 1
 
1.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 17
21.0%
8 12
14.8%
2 11
13.6%
0 10
12.3%
7 7
8.6%
5 6
 
7.4%
3 6
 
7.4%
4 5
 
6.2%
6 4
 
4.9%
9 3
 
3.7%
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 86
96.6%
Hangul 3
 
3.4%

Most frequent character per script

Common
ValueCountFrequency (%)
1 17
19.8%
8 12
14.0%
2 11
12.8%
0 10
11.6%
7 7
8.1%
5 6
 
7.0%
3 6
 
7.0%
4 5
 
5.8%
6 4
 
4.7%
, 4
 
4.7%
Other values (2) 4
 
4.7%
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%
8 12
14.0%
2 11
12.8%
0 10
11.6%
7 7
8.1%
5 6
 
7.0%
3 6
 
7.0%
4 5
 
5.8%
6 4
 
4.7%
, 4
 
4.7%
Other values (2) 4
 
4.7%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 14
Text

MISSING 

Distinct26
Distinct (%)78.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:41:01.655785image/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 row운암1동
2nd row7,454
3rd row19,332
4th row28
5th row18
ValueCountFrequency (%)
0 7
21.2%
49 2
 
6.1%
106 1
 
3.0%
27 1
 
3.0%
19,265 1
 
3.0%
7,462 1
 
3.0%
1 1
 
3.0%
67 1
 
3.0%
8 1
 
3.0%
9 1
 
3.0%
Other values (16) 16
48.5%
2024-02-10T09:41:02.472728image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

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

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 12
17.6%
0 8
11.8%
2 8
11.8%
9 7
10.3%
7 7
10.3%
4 6
8.8%
8 6
8.8%
6 6
8.8%
5 4
 
5.9%
3 4
 
5.9%
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 74
96.1%
Hangul 3
 
3.9%

Most frequent character per script

Common
ValueCountFrequency (%)
1 12
16.2%
0 8
10.8%
2 8
10.8%
9 7
9.5%
7 7
9.5%
4 6
8.1%
8 6
8.1%
6 6
8.1%
, 4
 
5.4%
5 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 8
10.8%
2 8
10.8%
9 7
9.5%
7 7
9.5%
4 6
8.1%
8 6
8.1%
6 6
8.1%
, 4
 
5.4%
5 4
 
5.4%
Other values (2) 6
8.1%
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
2024-02-10T09:41:02.810400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.2727273
Min length1

Characters and Unicode

Total characters75
Distinct characters15
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique22 ?
Unique (%)66.7%

Sample

1st row운암2동
2nd row6,131
3rd row12,000
4th row56
5th row7
ValueCountFrequency (%)
0 7
21.2%
7 2
 
6.1%
56 2
 
6.1%
4 1
 
3.0%
95 1
 
3.0%
11,950 1
 
3.0%
6,126 1
 
3.0%
1 1
 
3.0%
50 1
 
3.0%
5 1
 
3.0%
Other values (15) 15
45.5%
2024-02-10T09:41:03.633233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 13
17.3%
5 11
14.7%
1 10
13.3%
6 8
10.7%
9 5
 
6.7%
7 4
 
5.3%
, 4
 
5.3%
8 4
 
5.3%
4 4
 
5.3%
3 3
 
4.0%
Other values (5) 9
12.0%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 13
20.0%
5 11
16.9%
1 10
15.4%
6 8
12.3%
9 5
 
7.7%
7 4
 
6.2%
8 4
 
6.2%
4 4
 
6.2%
3 3
 
4.6%
2 3
 
4.6%
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 72
96.0%
Hangul 3
 
4.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 13
18.1%
5 11
15.3%
1 10
13.9%
6 8
11.1%
9 5
 
6.9%
7 4
 
5.6%
, 4
 
5.6%
8 4
 
5.6%
4 4
 
5.6%
3 3
 
4.2%
Other values (2) 6
8.3%
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 13
18.1%
5 11
15.3%
1 10
13.9%
6 8
11.1%
9 5
 
6.9%
7 4
 
5.6%
, 4
 
5.6%
8 4
 
5.6%
4 4
 
5.6%
3 3
 
4.2%
Other values (2) 6
8.3%
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
2024-02-10T09:41:04.117859image/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 row5,086
3rd row12,648
4th row31
5th row15
ValueCountFrequency (%)
0 7
21.2%
75 2
 
6.1%
15 2
 
6.1%
49 2
 
6.1%
5,086 1
 
3.0%
31 1
 
3.0%
12,648 1
 
3.0%
12,576 1
 
3.0%
5,077 1
 
3.0%
1 1
 
3.0%
Other values (14) 14
42.4%
2024-02-10T09:41:04.971051image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 12
15.8%
0 10
13.2%
4 8
10.5%
5 8
10.5%
7 6
7.9%
3 6
7.9%
6 5
6.6%
2 5
6.6%
9 4
 
5.3%
, 4
 
5.3%
Other values (5) 8
10.5%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 12
18.2%
0 10
15.2%
4 8
12.1%
5 8
12.1%
7 6
9.1%
3 6
9.1%
6 5
7.6%
2 5
7.6%
9 4
 
6.1%
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 (%)
1 12
16.4%
0 10
13.7%
4 8
11.0%
5 8
11.0%
7 6
8.2%
3 6
8.2%
6 5
6.8%
2 5
6.8%
9 4
 
5.5%
, 4
 
5.5%
Other values (2) 5
6.8%
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 10
13.7%
4 8
11.0%
5 8
11.0%
7 6
8.2%
3 6
8.2%
6 5
6.8%
2 5
6.8%
9 4
 
5.5%
, 4
 
5.5%
Other values (2) 5
6.8%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 17
Text

MISSING 

Distinct28
Distinct (%)84.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:41:05.344392image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.5454545
Min length1

Characters and Unicode

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

Unique

Unique26 ?
Unique (%)78.8%

Sample

1st row동림동
2nd row9,842
3rd row23,231
4th row56
5th row8
ValueCountFrequency (%)
0 5
 
15.2%
1 2
 
6.1%
8 2
 
6.1%
159 1
 
3.0%
194 1
 
3.0%
23,135 1
 
3.0%
9,828 1
 
3.0%
96 1
 
3.0%
14 1
 
3.0%
3 1
 
3.0%
Other values (17) 17
51.5%
2024-02-10T09:41:06.331776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 18
21.4%
3 10
11.9%
5 10
11.9%
2 9
10.7%
9 7
 
8.3%
0 6
 
7.1%
8 5
 
6.0%
4 5
 
6.0%
, 4
 
4.8%
6 3
 
3.6%
Other values (4) 7
 
8.3%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 18
24.3%
3 10
13.5%
5 10
13.5%
2 9
12.2%
9 7
 
9.5%
0 6
 
8.1%
8 5
 
6.8%
4 5
 
6.8%
6 3
 
4.1%
7 1
 
1.4%
Other Letter
ValueCountFrequency (%)
2
66.7%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
1 18
22.2%
3 10
12.3%
5 10
12.3%
2 9
11.1%
9 7
 
8.6%
0 6
 
7.4%
8 5
 
6.2%
4 5
 
6.2%
, 4
 
4.9%
6 3
 
3.7%
Other values (2) 4
 
4.9%
Hangul
ValueCountFrequency (%)
2
66.7%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 18
22.2%
3 10
12.3%
5 10
12.3%
2 9
11.1%
9 7
 
8.6%
0 6
 
7.4%
8 5
 
6.2%
4 5
 
6.2%
, 4
 
4.9%
6 3
 
3.7%
Other values (2) 4
 
4.9%
Hangul
ValueCountFrequency (%)
2
66.7%
1
33.3%

Unnamed: 18
Text

MISSING 

Distinct21
Distinct (%)63.6%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:41:06.726200image/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

Unique17 ?
Unique (%)51.5%

Sample

1st row우산동
2nd row5,634
3rd row10,239
4th row63
5th row9
ValueCountFrequency (%)
0 9
27.3%
63 3
 
9.1%
9 2
 
6.1%
5,634 2
 
6.1%
54 1
 
3.0%
10,239 1
 
3.0%
6 1
 
3.0%
11 1
 
3.0%
29 1
 
3.0%
36 1
 
3.0%
Other values (11) 11
33.3%
2024-02-10T09:41:07.740526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 12
16.9%
0 11
15.5%
1 9
12.7%
6 8
11.3%
5 7
9.9%
4 5
7.0%
2 5
7.0%
9 4
 
5.6%
, 4
 
5.6%
1
 
1.4%
Other values (5) 5
7.0%

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 (%)
3 12
19.0%
0 11
17.5%
1 9
14.3%
6 8
12.7%
5 7
11.1%
4 5
7.9%
2 5
7.9%
9 4
 
6.3%
8 1
 
1.6%
7 1
 
1.6%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
3 12
17.6%
0 11
16.2%
1 9
13.2%
6 8
11.8%
5 7
10.3%
4 5
7.4%
2 5
7.4%
9 4
 
5.9%
, 4
 
5.9%
8 1
 
1.5%
Other values (2) 2
 
2.9%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 12
17.6%
0 11
16.2%
1 9
13.2%
6 8
11.8%
5 7
10.3%
4 5
7.4%
2 5
7.4%
9 4
 
5.9%
, 4
 
5.9%
8 1
 
1.5%
Other values (2) 2
 
2.9%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 19
Text

MISSING 

Distinct20
Distinct (%)60.6%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:41:08.146273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
Mean length2.030303
Min length1

Characters and Unicode

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

Unique

Unique15 ?
Unique (%)45.5%

Sample

1st row풍향동
2nd row2,755
3rd row5,699
4th row24
5th row3
ValueCountFrequency (%)
0 8
24.2%
3 3
 
9.1%
24 3
 
9.1%
44 2
 
6.1%
42 2
 
6.1%
풍향동 1
 
3.0%
84 1
 
3.0%
5,699 1
 
3.0%
41 1
 
3.0%
19 1
 
3.0%
Other values (10) 10
30.3%
2024-02-10T09:41:09.117480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4 11
16.4%
0 9
13.4%
2 9
13.4%
5 7
10.4%
3 6
9.0%
, 4
 
6.0%
7 4
 
6.0%
1 4
 
6.0%
9 4
 
6.0%
8 3
 
4.5%
Other values (5) 6
9.0%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 11
18.6%
0 9
15.3%
2 9
15.3%
5 7
11.9%
3 6
10.2%
7 4
 
6.8%
1 4
 
6.8%
9 4
 
6.8%
8 3
 
5.1%
6 2
 
3.4%
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 64
95.5%
Hangul 3
 
4.5%

Most frequent character per script

Common
ValueCountFrequency (%)
4 11
17.2%
0 9
14.1%
2 9
14.1%
5 7
10.9%
3 6
9.4%
, 4
 
6.2%
7 4
 
6.2%
1 4
 
6.2%
9 4
 
6.2%
8 3
 
4.7%
Other values (2) 3
 
4.7%
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 (%)
4 11
17.2%
0 9
14.1%
2 9
14.1%
5 7
10.9%
3 6
9.4%
, 4
 
6.2%
7 4
 
6.2%
1 4
 
6.2%
9 4
 
6.2%
8 3
 
4.7%
Other values (2) 3
 
4.7%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 20
Text

MISSING 

Distinct24
Distinct (%)72.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:41:09.527435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.4545455
Min length1

Characters and Unicode

Total characters81
Distinct characters15
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique20 ?
Unique (%)60.6%

Sample

1st row문화동
2nd row9,735
3rd row20,848
4th row58
5th row7
ValueCountFrequency (%)
0 7
21.2%
7 2
 
6.1%
58 2
 
6.1%
85 2
 
6.1%
152 1
 
3.0%
20,848 1
 
3.0%
194 1
 
3.0%
20,727 1
 
3.0%
9,712 1
 
3.0%
1 1
 
3.0%
Other values (14) 14
42.4%
2024-02-10T09:41:10.597579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 11
13.6%
1 11
13.6%
2 10
12.3%
5 9
11.1%
7 8
9.9%
8 7
8.6%
9 6
7.4%
, 4
 
4.9%
3 4
 
4.9%
4 3
 
3.7%
Other values (5) 8
9.9%

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 (%)
0 11
15.5%
1 11
15.5%
2 10
14.1%
5 9
12.7%
7 8
11.3%
8 7
9.9%
9 6
8.5%
3 4
 
5.6%
4 3
 
4.2%
6 2
 
2.8%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
0 11
14.1%
1 11
14.1%
2 10
12.8%
5 9
11.5%
7 8
10.3%
8 7
9.0%
9 6
7.7%
, 4
 
5.1%
3 4
 
5.1%
4 3
 
3.8%
Other values (2) 5
6.4%
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 (%)
0 11
14.1%
1 11
14.1%
2 10
12.8%
5 9
11.5%
7 8
10.3%
8 7
9.0%
9 6
7.7%
, 4
 
5.1%
3 4
 
5.1%
4 3
 
3.8%
Other values (2) 5
6.4%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 21
Text

MISSING 

Distinct22
Distinct (%)66.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:41:10.996948image/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

Unique17 ?
Unique (%)51.5%

Sample

1st row문흥1동
2nd row6,493
3rd row15,904
4th row29
5th row9
ValueCountFrequency (%)
0 8
24.2%
62 2
 
6.1%
29 2
 
6.1%
9 2
 
6.1%
30 2
 
6.1%
44 1
 
3.0%
122 1
 
3.0%
6,481 1
 
3.0%
95 1
 
3.0%
12 1
 
3.0%
Other values (12) 12
36.4%
2024-02-10T09:41:12.205026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 14
18.4%
9 13
17.1%
2 8
10.5%
1 8
10.5%
4 7
9.2%
6 6
7.9%
3 4
 
5.3%
5 4
 
5.3%
, 4
 
5.3%
8 3
 
3.9%
Other values (4) 5
 
6.6%

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 (%)
0 14
20.9%
9 13
19.4%
2 8
11.9%
1 8
11.9%
4 7
10.4%
6 6
9.0%
3 4
 
6.0%
5 4
 
6.0%
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 (%)
- 2
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
0 14
19.2%
9 13
17.8%
2 8
11.0%
1 8
11.0%
4 7
9.6%
6 6
8.2%
3 4
 
5.5%
5 4
 
5.5%
, 4
 
5.5%
8 3
 
4.1%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 14
19.2%
9 13
17.8%
2 8
11.0%
1 8
11.0%
4 7
9.6%
6 6
8.2%
3 4
 
5.5%
5 4
 
5.5%
, 4
 
5.5%
8 3
 
4.1%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 22
Text

MISSING 

Distinct26
Distinct (%)78.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:41:12.653842image/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

Unique23 ?
Unique (%)69.7%

Sample

1st row문흥2동
2nd row7,372
3rd row15,648
4th row32
5th row4
ValueCountFrequency (%)
0 6
 
18.2%
1 2
 
6.1%
4 2
 
6.1%
126 1
 
3.0%
233 1
 
3.0%
15,594 1
 
3.0%
7,383 1
 
3.0%
54 1
 
3.0%
11 1
 
3.0%
10 1
 
3.0%
Other values (16) 16
48.5%
2024-02-10T09:41:13.719042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 15
19.5%
0 9
11.7%
3 9
11.7%
5 8
10.4%
2 7
9.1%
4 6
 
7.8%
8 5
 
6.5%
7 4
 
5.2%
, 4
 
5.2%
6 3
 
3.9%
Other values (5) 7
9.1%

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 (%)
1 15
21.7%
0 9
13.0%
3 9
13.0%
5 8
11.6%
2 7
10.1%
4 6
 
8.7%
8 5
 
7.2%
7 4
 
5.8%
6 3
 
4.3%
9 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 (%)
1 15
20.3%
0 9
12.2%
3 9
12.2%
5 8
10.8%
2 7
9.5%
4 6
 
8.1%
8 5
 
6.8%
7 4
 
5.4%
, 4
 
5.4%
6 3
 
4.1%
Other values (2) 4
 
5.4%
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 15
20.3%
0 9
12.2%
3 9
12.2%
5 8
10.8%
2 7
9.5%
4 6
 
8.1%
8 5
 
6.8%
7 4
 
5.4%
, 4
 
5.4%
6 3
 
4.1%
Other values (2) 4
 
5.4%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 23
Text

MISSING 

Distinct23
Distinct (%)69.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:41:14.133703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length2.1212121
Min length1

Characters and Unicode

Total characters70
Distinct characters15
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique19 ?
Unique (%)57.6%

Sample

1st row두암1동
2nd row4,022
3rd row7,759
4th row22
5th row7
ValueCountFrequency (%)
0 8
24.2%
7 2
 
6.1%
22 2
 
6.1%
23 2
 
6.1%
52 2
 
6.1%
21 1
 
3.0%
7,759 1
 
3.0%
4,022 1
 
3.0%
4,013 1
 
3.0%
9 1
 
3.0%
Other values (12) 12
36.4%
2024-02-10T09:41:15.320592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 14
20.0%
0 12
17.1%
3 8
11.4%
4 7
10.0%
7 6
8.6%
5 4
 
5.7%
1 4
 
5.7%
, 4
 
5.7%
8 3
 
4.3%
- 2
 
2.9%
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 (%)
2 14
23.0%
0 12
19.7%
3 8
13.1%
4 7
11.5%
7 6
9.8%
5 4
 
6.6%
1 4
 
6.6%
8 3
 
4.9%
9 2
 
3.3%
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 (%)
2 14
20.9%
0 12
17.9%
3 8
11.9%
4 7
10.4%
7 6
9.0%
5 4
 
6.0%
1 4
 
6.0%
, 4
 
6.0%
8 3
 
4.5%
- 2
 
3.0%
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 (%)
2 14
20.9%
0 12
17.9%
3 8
11.9%
4 7
10.4%
7 6
9.0%
5 4
 
6.0%
1 4
 
6.0%
, 4
 
6.0%
8 3
 
4.5%
- 2
 
3.0%
Other values (2) 3
 
4.5%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 24
Text

MISSING 

Distinct26
Distinct (%)78.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:41:15.805140image/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 row두암2동
2nd row7,711
3rd row16,002
4th row52
5th row9
ValueCountFrequency (%)
0 7
21.2%
9 2
 
6.1%
113 1
 
3.0%
15,934 1
 
3.0%
7,689 1
 
3.0%
4 1
 
3.0%
68 1
 
3.0%
22 1
 
3.0%
12 1
 
3.0%
61 1
 
3.0%
Other values (16) 16
48.5%
2024-02-10T09:41:16.743498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 13
16.9%
0 10
13.0%
2 8
10.4%
7 8
10.4%
9 7
9.1%
6 6
7.8%
4 5
 
6.5%
5 5
 
6.5%
, 4
 
5.2%
3 3
 
3.9%
Other values (5) 8
10.4%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 13
19.1%
0 10
14.7%
2 8
11.8%
7 8
11.8%
9 7
10.3%
6 6
8.8%
4 5
 
7.4%
5 5
 
7.4%
3 3
 
4.4%
8 3
 
4.4%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
1 13
17.6%
0 10
13.5%
2 8
10.8%
7 8
10.8%
9 7
9.5%
6 6
8.1%
4 5
 
6.8%
5 5
 
6.8%
, 4
 
5.4%
3 3
 
4.1%
Other values (2) 5
 
6.8%
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 13
17.6%
0 10
13.5%
2 8
10.8%
7 8
10.8%
9 7
9.5%
6 6
8.1%
4 5
 
6.8%
5 5
 
6.8%
, 4
 
5.4%
3 3
 
4.1%
Other values (2) 5
 
6.8%
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
2024-02-10T09:41:17.232919image/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 row두암3동
2nd row7,805
3rd row13,313
4th row49
5th row7
ValueCountFrequency (%)
0 7
21.2%
44 2
 
6.1%
7 2
 
6.1%
47 2
 
6.1%
71 1
 
3.0%
49 1
 
3.0%
99 1
 
3.0%
7,778 1
 
3.0%
2 1
 
3.0%
65 1
 
3.0%
Other values (14) 14
42.4%
2024-02-10T09:41:18.171167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
7 12
16.0%
4 9
12.0%
3 9
12.0%
0 8
10.7%
1 6
8.0%
2 5
6.7%
6 4
 
5.3%
, 4
 
5.3%
5 4
 
5.3%
9 4
 
5.3%
Other values (5) 10
13.3%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
7 12
18.5%
4 9
13.8%
3 9
13.8%
0 8
12.3%
1 6
9.2%
2 5
7.7%
6 4
 
6.2%
5 4
 
6.2%
9 4
 
6.2%
8 4
 
6.2%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
7 12
16.7%
4 9
12.5%
3 9
12.5%
0 8
11.1%
1 6
8.3%
2 5
6.9%
6 4
 
5.6%
, 4
 
5.6%
5 4
 
5.6%
9 4
 
5.6%
Other values (2) 7
9.7%
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 (%)
7 12
16.7%
4 9
12.5%
3 9
12.5%
0 8
11.1%
1 6
8.3%
2 5
6.9%
6 4
 
5.6%
, 4
 
5.6%
5 4
 
5.6%
9 4
 
5.6%
Other values (2) 7
9.7%
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
2024-02-10T09:41:18.620676image/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

Unique20 ?
Unique (%)60.6%

Sample

1st row삼각동
2nd row6,066
3rd row14,040
4th row29
5th row4
ValueCountFrequency (%)
0 7
21.2%
31 2
 
6.1%
4 2
 
6.1%
9 2
 
6.1%
129 1
 
3.0%
29 1
 
3.0%
152 1
 
3.0%
6,049 1
 
3.0%
2 1
 
3.0%
101 1
 
3.0%
Other values (14) 14
42.4%
2024-02-10T09:41:19.623581image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 13
16.9%
1 12
15.6%
9 8
10.4%
2 8
10.4%
3 7
9.1%
4 6
7.8%
6 5
 
6.5%
, 4
 
5.2%
5 4
 
5.2%
7 3
 
3.9%
Other values (5) 7
9.1%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 13
19.1%
1 12
17.6%
9 8
11.8%
2 8
11.8%
3 7
10.3%
4 6
8.8%
6 5
 
7.4%
5 4
 
5.9%
7 3
 
4.4%
8 2
 
2.9%
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 74
96.1%
Hangul 3
 
3.9%

Most frequent character per script

Common
ValueCountFrequency (%)
0 13
17.6%
1 12
16.2%
9 8
10.8%
2 8
10.8%
3 7
9.5%
4 6
8.1%
6 5
 
6.8%
, 4
 
5.4%
5 4
 
5.4%
7 3
 
4.1%
Other values (2) 4
 
5.4%
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 13
17.6%
1 12
16.2%
9 8
10.8%
2 8
10.8%
3 7
9.5%
4 6
8.1%
6 5
 
6.8%
, 4
 
5.4%
5 4
 
5.4%
7 3
 
4.1%
Other values (2) 4
 
5.4%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 27
Text

MISSING 

Distinct23
Distinct (%)69.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:41:19.947195image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length4
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

Unique19 ?
Unique (%)57.6%

Sample

1st row일곡동
2nd row11,559
3rd row29,827
4th row33
5th row11
ValueCountFrequency (%)
0 8
24.2%
11 2
 
6.1%
106 2
 
6.1%
33 2
 
6.1%
188 1
 
3.0%
213 1
 
3.0%
11,550 1
 
3.0%
190 1
 
3.0%
9 1
 
3.0%
17 1
 
3.0%
Other values (13) 13
39.4%
2024-02-10T09:41:20.964205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 18
21.2%
0 12
14.1%
9 9
10.6%
2 9
10.6%
3 8
9.4%
5 6
 
7.1%
6 4
 
4.7%
, 4
 
4.7%
8 4
 
4.7%
7 4
 
4.7%
Other values (5) 7
 
8.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 76
89.4%
Other Punctuation 4
 
4.7%
Other Letter 3
 
3.5%
Dash Punctuation 2
 
2.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 18
23.7%
0 12
15.8%
9 9
11.8%
2 9
11.8%
3 8
10.5%
5 6
 
7.9%
6 4
 
5.3%
8 4
 
5.3%
7 4
 
5.3%
4 2
 
2.6%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
1 18
22.0%
0 12
14.6%
9 9
11.0%
2 9
11.0%
3 8
9.8%
5 6
 
7.3%
6 4
 
4.9%
, 4
 
4.9%
8 4
 
4.9%
7 4
 
4.9%
Other values (2) 4
 
4.9%
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 18
22.0%
0 12
14.6%
9 9
11.0%
2 9
11.0%
3 8
9.8%
5 6
 
7.3%
6 4
 
4.9%
, 4
 
4.9%
8 4
 
4.9%
7 4
 
4.9%
Other values (2) 4
 
4.9%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 28
Text

MISSING 

Distinct23
Distinct (%)69.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:41:21.387226image/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 row매곡동
2nd row5,525
3rd row13,852
4th row21
5th row5
ValueCountFrequency (%)
0 8
24.2%
5 2
 
6.1%
21 2
 
6.1%
7 2
 
6.1%
97 1
 
3.0%
13,852 1
 
3.0%
96 1
 
3.0%
5,515 1
 
3.0%
86 1
 
3.0%
10 1
 
3.0%
Other values (13) 13
39.4%
2024-02-10T09:41:22.289681image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 13
17.8%
0 11
15.1%
1 9
12.3%
7 6
8.2%
2 6
8.2%
9 5
 
6.8%
8 4
 
5.5%
, 4
 
5.5%
3 4
 
5.5%
6 4
 
5.5%
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 (%)
5 13
20.3%
0 11
17.2%
1 9
14.1%
7 6
9.4%
2 6
9.4%
9 5
 
7.8%
8 4
 
6.2%
3 4
 
6.2%
6 4
 
6.2%
4 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 (%)
5 13
18.6%
0 11
15.7%
1 9
12.9%
7 6
8.6%
2 6
8.6%
9 5
 
7.1%
8 4
 
5.7%
, 4
 
5.7%
3 4
 
5.7%
6 4
 
5.7%
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 13
18.6%
0 11
15.7%
1 9
12.9%
7 6
8.6%
2 6
8.6%
9 5
 
7.1%
8 4
 
5.7%
, 4
 
5.7%
3 4
 
5.7%
6 4
 
5.7%
Other values (2) 4
 
5.7%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 29
Text

MISSING 

Distinct24
Distinct (%)72.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:41:22.675931image/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

Unique21 ?
Unique (%)63.6%

Sample

1st row오치1동
2nd row5,532
3rd row10,912
4th row46
5th row8
ValueCountFrequency (%)
0 8
24.2%
46 2
 
6.1%
48 2
 
6.1%
8 2
 
6.1%
67 1
 
3.0%
10,912 1
 
3.0%
93 1
 
3.0%
5,525 1
 
3.0%
7 1
 
3.0%
11 1
 
3.0%
Other values (13) 13
39.4%
2024-02-10T09:41:23.687426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

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

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 10
15.4%
5 9
13.8%
1 8
12.3%
8 7
10.8%
4 7
10.8%
6 7
10.8%
7 5
7.7%
3 5
7.7%
2 4
 
6.2%
9 3
 
4.6%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
0 10
14.1%
5 9
12.7%
1 8
11.3%
8 7
9.9%
4 7
9.9%
6 7
9.9%
7 5
7.0%
3 5
7.0%
2 4
 
5.6%
, 4
 
5.6%
Other values (2) 5
7.0%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 10
14.1%
5 9
12.7%
1 8
11.3%
8 7
9.9%
4 7
9.9%
6 7
9.9%
7 5
7.0%
3 5
7.0%
2 4
 
5.6%
, 4
 
5.6%
Other values (2) 5
7.0%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 30
Text

MISSING 

Distinct24
Distinct (%)72.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:41:24.097772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.1818182
Min length1

Characters and Unicode

Total characters72
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

Unique21 ?
Unique (%)63.6%

Sample

1st row오치2동
2nd row7,008
3rd row12,448
4th row34
5th row8
ValueCountFrequency (%)
0 8
24.2%
34 2
 
6.1%
8 2
 
6.1%
69 1
 
3.0%
12,448 1
 
3.0%
75 1
 
3.0%
7,013 1
 
3.0%
14 1
 
3.0%
5 1
 
3.0%
12 1
 
3.0%
Other values (14) 14
42.4%
2024-02-10T09:41:25.121027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 13
18.1%
1 9
12.5%
7 9
12.5%
4 8
11.1%
8 6
8.3%
6 6
8.3%
2 6
8.3%
3 5
 
6.9%
, 4
 
5.6%
5 2
 
2.8%
Other values (4) 4
 
5.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 65
90.3%
Other Punctuation 4
 
5.6%
Other Letter 3
 
4.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 13
20.0%
1 9
13.8%
7 9
13.8%
4 8
12.3%
8 6
9.2%
6 6
9.2%
2 6
9.2%
3 5
 
7.7%
5 2
 
3.1%
9 1
 
1.5%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
0 13
18.8%
1 9
13.0%
7 9
13.0%
4 8
11.6%
8 6
8.7%
6 6
8.7%
2 6
8.7%
3 5
 
7.2%
, 4
 
5.8%
5 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 13
18.8%
1 9
13.0%
7 9
13.0%
4 8
11.6%
8 6
8.7%
6 6
8.7%
2 6
8.7%
3 5
 
7.2%
, 4
 
5.8%
5 2
 
2.9%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 31
Text

MISSING 

Distinct21
Distinct (%)63.6%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:41:25.544614image/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 categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique15 ?
Unique (%)45.5%

Sample

1st row석곡동
2nd row1,384
3rd row2,503
4th row21
5th row3
ValueCountFrequency (%)
0 8
24.2%
21 2
 
6.1%
3 2
 
6.1%
9 2
 
6.1%
10 2
 
6.1%
5 2
 
6.1%
13 1
 
3.0%
1 1
 
3.0%
1,389 1
 
3.0%
2 1
 
3.0%
Other values (11) 11
33.3%
2024-02-10T09:41:26.537711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 12
19.7%
1 12
19.7%
2 7
11.5%
3 7
11.5%
5 4
 
6.6%
9 4
 
6.6%
, 4
 
6.6%
8 4
 
6.6%
4 3
 
4.9%
1
 
1.6%
Other values (3) 3
 
4.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 54
88.5%
Other Punctuation 4
 
6.6%
Other Letter 3
 
4.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 12
22.2%
1 12
22.2%
2 7
13.0%
3 7
13.0%
5 4
 
7.4%
9 4
 
7.4%
8 4
 
7.4%
4 3
 
5.6%
6 1
 
1.9%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
0 12
20.7%
1 12
20.7%
2 7
12.1%
3 7
12.1%
5 4
 
6.9%
9 4
 
6.9%
, 4
 
6.9%
8 4
 
6.9%
4 3
 
5.2%
6 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 (%)
0 12
20.7%
1 12
20.7%
2 7
12.1%
3 7
12.1%
5 4
 
6.9%
9 4
 
6.9%
, 4
 
6.9%
8 4
 
6.9%
4 3
 
5.2%
6 1
 
1.7%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 32
Text

MISSING 

Distinct25
Distinct (%)75.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:41:26.882649image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
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

Unique22 ?
Unique (%)66.7%

Sample

1st row건국동
2nd row9,245
3rd row22,274
4th row63
5th row14
ValueCountFrequency (%)
0 7
21.2%
15 2
 
6.1%
63 2
 
6.1%
151 1
 
3.0%
22,274 1
 
3.0%
14 1
 
3.0%
22,201 1
 
3.0%
9,216 1
 
3.0%
73 1
 
3.0%
29 1
 
3.0%
Other values (15) 15
45.5%
2024-02-10T09:41:27.760996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 15
18.3%
2 12
14.6%
0 10
12.2%
5 8
9.8%
3 6
 
7.3%
9 6
 
7.3%
6 4
 
4.9%
7 4
 
4.9%
8 4
 
4.9%
, 4
 
4.9%
Other values (5) 9
11.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 73
89.0%
Other Punctuation 4
 
4.9%
Other Letter 3
 
3.7%
Dash Punctuation 2
 
2.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 15
20.5%
2 12
16.4%
0 10
13.7%
5 8
11.0%
3 6
 
8.2%
9 6
 
8.2%
6 4
 
5.5%
7 4
 
5.5%
8 4
 
5.5%
4 4
 
5.5%
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 79
96.3%
Hangul 3
 
3.7%

Most frequent character per script

Common
ValueCountFrequency (%)
1 15
19.0%
2 12
15.2%
0 10
12.7%
5 8
10.1%
3 6
 
7.6%
9 6
 
7.6%
6 4
 
5.1%
7 4
 
5.1%
8 4
 
5.1%
, 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 15
19.0%
2 12
15.2%
0 10
12.7%
5 8
10.1%
3 6
 
7.6%
9 6
 
7.6%
6 4
 
5.1%
7 4
 
5.1%
8 4
 
5.1%
, 4
 
5.1%
Other values (2) 6
 
7.6%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 33
Text

MISSING 

Distinct27
Distinct (%)81.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:41:28.253869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length4
Mean length2.7272727
Min length1

Characters and Unicode

Total characters90
Distinct characters15
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique25 ?
Unique (%)75.8%

Sample

1st row양산동
2nd row16,419
3rd row37,855
4th row64
5th row19
ValueCountFrequency (%)
0 6
 
18.2%
19 2
 
6.1%
264 1
 
3.0%
495 1
 
3.0%
37,705 1
 
3.0%
16,405 1
 
3.0%
1 1
 
3.0%
150 1
 
3.0%
14 1
 
3.0%
22 1
 
3.0%
Other values (17) 17
51.5%
2024-02-10T09:41:29.016752image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 17
18.9%
0 11
12.2%
4 8
8.9%
5 8
8.9%
6 7
7.8%
3 7
7.8%
9 6
 
6.7%
2 6
 
6.7%
7 6
 
6.7%
, 4
 
4.4%
Other values (5) 10
11.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 80
88.9%
Other Punctuation 4
 
4.4%
Dash Punctuation 3
 
3.3%
Other Letter 3
 
3.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 17
21.2%
0 11
13.8%
4 8
10.0%
5 8
10.0%
6 7
8.8%
3 7
8.8%
9 6
 
7.5%
2 6
 
7.5%
7 6
 
7.5%
8 4
 
5.0%
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 87
96.7%
Hangul 3
 
3.3%

Most frequent character per script

Common
ValueCountFrequency (%)
1 17
19.5%
0 11
12.6%
4 8
9.2%
5 8
9.2%
6 7
8.0%
3 7
8.0%
9 6
 
6.9%
2 6
 
6.9%
7 6
 
6.9%
, 4
 
4.6%
Other values (2) 7
8.0%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 17
19.5%
0 11
12.6%
4 8
9.2%
5 8
9.2%
6 7
8.0%
3 7
8.0%
9 6
 
6.9%
2 6
 
6.9%
7 6
 
6.9%
, 4
 
4.6%
Other values (2) 7
8.0%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 34
Text

MISSING 

Distinct25
Distinct (%)75.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:41:29.418880image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length3
Mean length2.4545455
Min length1

Characters and Unicode

Total characters81
Distinct characters15
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique23 ?
Unique (%)69.7%

Sample

1st row신용동
2nd row11,838
3rd row29,781
4th row8
5th row9
ValueCountFrequency (%)
0 8
24.2%
8 2
 
6.1%
159 1
 
3.0%
322 1
 
3.0%
29,717 1
 
3.0%
11,823 1
 
3.0%
64 1
 
3.0%
15 1
 
3.0%
5 1
 
3.0%
108 1
 
3.0%
Other values (15) 15
45.5%
2024-02-10T09:41:30.426398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 16
19.8%
2 12
14.8%
0 11
13.6%
8 9
11.1%
9 7
8.6%
3 5
 
6.2%
, 4
 
4.9%
7 4
 
4.9%
6 3
 
3.7%
5 3
 
3.7%
Other values (5) 7
8.6%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 16
22.2%
2 12
16.7%
0 11
15.3%
8 9
12.5%
9 7
9.7%
3 5
 
6.9%
7 4
 
5.6%
6 3
 
4.2%
5 3
 
4.2%
4 2
 
2.8%
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 78
96.3%
Hangul 3
 
3.7%

Most frequent character per script

Common
ValueCountFrequency (%)
1 16
20.5%
2 12
15.4%
0 11
14.1%
8 9
11.5%
9 7
9.0%
3 5
 
6.4%
, 4
 
5.1%
7 4
 
5.1%
6 3
 
3.8%
5 3
 
3.8%
Other values (2) 4
 
5.1%
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 16
20.5%
2 12
15.4%
0 11
14.1%
8 9
11.5%
9 7
9.0%
3 5
 
6.4%
, 4
 
5.1%
7 4
 
5.1%
6 3
 
3.8%
5 3
 
3.8%
Other values (2) 4
 
5.1%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Sample

Unnamed: 0인구이동보고서(1호)Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 6Unnamed: 7Unnamed: 8Unnamed: 9Unnamed: 10Unnamed: 11Unnamed: 12Unnamed: 13Unnamed: 14Unnamed: 15Unnamed: 16Unnamed: 17Unnamed: 18Unnamed: 19Unnamed: 20Unnamed: 21Unnamed: 22Unnamed: 23Unnamed: 24Unnamed: 25Unnamed: 26Unnamed: 27Unnamed: 28Unnamed: 29Unnamed: 30Unnamed: 31Unnamed: 32Unnamed: 33Unnamed: 34
0<NA>행정기관 :<NA>광주광역시 북구<NA><NA><NA><NA><NA><NA>출력일자 :<NA>2022.04.12<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
1<NA>작성기준 :<NA>2022.03 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>196,4463,0074,0423,1332,0154,5647,216<NA>17,8537,4546,1315,0869,8425,6342,7559,7356,4937,3724,0227,7117,8056,06611,5595,5255,5327,0081,3849,24516,41911,838
4<NA>전월말인구수<NA><NA><NA>427,1394,7917,5695,5083,0559,26512,361<NA>38,47519,33212,00012,64823,23110,2395,69920,84815,90415,6487,75916,00213,31314,04029,82713,85210,91212,4482,50322,27437,85529,781
5<NA>전월말거주불명자수<NA><NA><NA>1,280586341533784<NA>12528563156632458293222524929332146342163648
6<NA>전월말재외국민등록자수<NA><NA><NA>219043451<NA>1818715893794797411588314199
7<NA>증 가 요 인전 입<NA>6,22565696609634127245<NA>5591531537525211484194122183831569915223310312716729235337239
8<NA><NA><NA>남자<NA>3,1062635529732362123<NA>28871854110963428564954577448010655698711116177110
9<NA><NA><NA>여자<NA>3,1193934131231165122<NA>271826834143514210958883879557212748588018119160129
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>3000000<NA>0000300000000000000000
26<NA><NA>국외<NA><NA>0000000<NA>0000000000000000000000
27<NA><NA>기타<NA><NA>0000000<NA>0000000000000000000000
28<NA>세대수증감<NA><NA><NA>4732208179220-720<NA>418-5-9-1403-23-1211-9-22-27-17-9-10-755-29-14-15
29<NA>인구수증감<NA><NA><NA>39-19542444559-2734<NA>-67-67-50-72-96-6-17-121-95-54-23-68-65-101-190-86-48145-73-150-64
30<NA>거주불명자수증감<NA><NA><NA>-5-2-10-11-1<NA>0-1-1-1-100-10104-22000000-10
31<NA>금월말세대수<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
32<NA>금월말인구수<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
33<NA>금월말거주불명자수<NA><NA><NA>1,275566241523883<NA>12527553055632457293322564731332146342163638
34<NA>금월말재외국민등록자수<NA><NA><NA>220053451<NA>18197158937947974115883121910

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>국외<NA><NA>0000000<NA>00000000000000000000002
1<NA>기타<NA><NA>0000000<NA>00000000000000000000002