Overview

Dataset statistics

Number of variables3
Number of observations100
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.5 KiB
Average record size in memory25.3 B

Variable types

Text2
Categorical1

Alerts

지자체코드 has unique valuesUnique

Reproduction

Analysis started2023-12-10 12:26:55.820804
Analysis finished2023-12-10 12:26:56.342598
Duration0.52 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

지자체코드
Text

UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T21:26:56.646091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters300
Distinct characters36
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique100 ?
Unique (%)100.0%

Sample

1st rowW01
2nd rowW02
3rd rowW03
4th rowW04
5th rowW05
ValueCountFrequency (%)
w01 1
 
1.0%
w1t 1
 
1.0%
w24 1
 
1.0%
w23 1
 
1.0%
w22 1
 
1.0%
w21 1
 
1.0%
w20 1
 
1.0%
w1z 1
 
1.0%
w1y 1
 
1.0%
w1x 1
 
1.0%
Other values (90) 90
90.0%
2023-12-10T21:26:57.355165image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
W 103
34.3%
1 39
 
13.0%
0 37
 
12.3%
2 30
 
10.0%
3 9
 
3.0%
4 4
 
1.3%
G 3
 
1.0%
Y 3
 
1.0%
V 3
 
1.0%
T 3
 
1.0%
Other values (26) 66
22.0%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 166
55.3%
Decimal Number 134
44.7%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
W 103
62.0%
G 3
 
1.8%
Y 3
 
1.8%
V 3
 
1.8%
T 3
 
1.8%
S 3
 
1.8%
R 3
 
1.8%
P 3
 
1.8%
Q 3
 
1.8%
L 3
 
1.8%
Other values (16) 36
 
21.7%
Decimal Number
ValueCountFrequency (%)
1 39
29.1%
0 37
27.6%
2 30
22.4%
3 9
 
6.7%
4 4
 
3.0%
8 3
 
2.2%
5 3
 
2.2%
6 3
 
2.2%
7 3
 
2.2%
9 3
 
2.2%

Most occurring scripts

ValueCountFrequency (%)
Latin 166
55.3%
Common 134
44.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
W 103
62.0%
G 3
 
1.8%
Y 3
 
1.8%
V 3
 
1.8%
T 3
 
1.8%
S 3
 
1.8%
R 3
 
1.8%
P 3
 
1.8%
Q 3
 
1.8%
L 3
 
1.8%
Other values (16) 36
 
21.7%
Common
ValueCountFrequency (%)
1 39
29.1%
0 37
27.6%
2 30
22.4%
3 9
 
6.7%
4 4
 
3.0%
8 3
 
2.2%
5 3
 
2.2%
6 3
 
2.2%
7 3
 
2.2%
9 3
 
2.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 300
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
W 103
34.3%
1 39
 
13.0%
0 37
 
12.3%
2 30
 
10.0%
3 9
 
3.0%
4 4
 
1.3%
G 3
 
1.0%
Y 3
 
1.0%
V 3
 
1.0%
T 3
 
1.0%
Other values (26) 66
22.0%

지자체 시도명
Categorical

Distinct8
Distinct (%)8.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
경기도
28 
서울특별시
24 
부산광역시
16 
인천광역시
9 
대구광역시
8 
Other values (3)
15 

Length

Max length5
Median length5
Mean length4.44
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row서울특별시
2nd row서울특별시
3rd row서울특별시
4th row서울특별시
5th row서울특별시

Common Values

ValueCountFrequency (%)
경기도 28
28.0%
서울특별시 24
24.0%
부산광역시 16
16.0%
인천광역시 9
 
9.0%
대구광역시 8
 
8.0%
광주광역시 5
 
5.0%
대전광역시 5
 
5.0%
울산광역시 5
 
5.0%

Length

2023-12-10T21:26:57.618490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T21:26:57.821339image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경기도 28
28.0%
서울특별시 24
24.0%
부산광역시 16
16.0%
인천광역시 9
 
9.0%
대구광역시 8
 
8.0%
광주광역시 5
 
5.0%
대전광역시 5
 
5.0%
울산광역시 5
 
5.0%

지자체 시군구명
Text

Distinct79
Distinct (%)79.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T21:26:58.204762image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length3
Mean length3.05
Min length2

Characters and Unicode

Total characters305
Distinct characters80
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

Unique73 ?
Unique (%)73.0%

Sample

1st row종로구
2nd row중구
3rd row용산구
4th row성동구
5th row광진구
ValueCountFrequency (%)
중구 6
 
6.0%
동구 6
 
6.0%
서구 5
 
5.0%
남구 4
 
4.0%
북구 4
 
4.0%
강서구 2
 
2.0%
울주군 1
 
1.0%
수원시팔달구 1
 
1.0%
성남시중원구 1
 
1.0%
성남시수정구 1
 
1.0%
Other values (69) 69
69.0%
2023-12-10T21:26:59.089825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
구 77
25.2%
시 29
 
9.5%
동 13
 
4.3%
남 11
 
3.6%
서 10
 
3.3%
성 10
 
3.3%
중 8
 
2.6%
수 8
 
2.6%
북 6
 
2.0%
강 6
 
2.0%
Other values (70) 127
41.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 305
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 77
25.2%
시 29
 
9.5%
동 13
 
4.3%
남 11
 
3.6%
서 10
 
3.3%
성 10
 
3.3%
중 8
 
2.6%
수 8
 
2.6%
북 6
 
2.0%
강 6
 
2.0%
Other values (70) 127
41.6%

Most occurring scripts

ValueCountFrequency (%)
Hangul 305
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 77
25.2%
시 29
 
9.5%
동 13
 
4.3%
남 11
 
3.6%
서 10
 
3.3%
성 10
 
3.3%
중 8
 
2.6%
수 8
 
2.6%
북 6
 
2.0%
강 6
 
2.0%
Other values (70) 127
41.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 305
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
구 77
25.2%
시 29
 
9.5%
동 13
 
4.3%
남 11
 
3.6%
서 10
 
3.3%
성 10
 
3.3%
중 8
 
2.6%
수 8
 
2.6%
북 6
 
2.0%
강 6
 
2.0%
Other values (70) 127
41.6%

Correlations

2023-12-10T21:26:59.265911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
지자체코드지자체 시도명지자체 시군구명
지자체코드1.0001.0001.000
지자체 시도명1.0001.0000.000
지자체 시군구명1.0000.0001.000

Missing values

2023-12-10T21:26:56.109342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T21:26:56.258077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

지자체코드지자체 시도명지자체 시군구명
0W01서울특별시종로구
1W02서울특별시중구
2W03서울특별시용산구
3W04서울특별시성동구
4W05서울특별시광진구
5W06서울특별시동대문구
6W07서울특별시중랑구
7W08서울특별시성북구
8W09서울특별시강북구
9W0A서울특별시도봉구
지자체코드지자체 시도명지자체 시군구명
90W2T경기도시흥시
91W2U경기도군포시
92W2V경기도의왕시
93W2W경기도하남시
94W2Y경기도용인시
95W30경기도파주시
96W31경기도이천시
97W32경기도안성시
98W33경기도김포시
99W34경기도화성시