Overview

Dataset statistics

Number of variables9
Number of observations229
Missing cells0
Missing cells (%)0.0%
Duplicate rows7
Duplicate rows (%)3.1%
Total size in memory18.0 KiB
Average record size in memory80.6 B

Variable types

Text1
Categorical8

Dataset

Description지하수 이용부담금 지자체별 부과,징수 실적에 대한 통계 데이터입니다.지자체별 지하수 부과 건수, 부과 금액, 징수 건수, 징수 금액, 징수율, 부과 건수와 징수 건수 차이, 부과 금액과 징수 금액 차이에 대한 정보를 제공합니다.
Author한국수자원공사
URLhttps://www.data.go.kr/data/15088330/fileData.do

Alerts

부과(A) has constant value ""Constant
징수(B) has constant value ""Constant
차이(A)-(B) has constant value ""Constant
건수1 has constant value ""Constant
금액1 has constant value ""Constant
건수2 has constant value ""Constant
금액2 has constant value ""Constant
징수율 has constant value ""Constant
Dataset has 7 (3.1%) duplicate rowsDuplicates

Reproduction

Analysis started2023-12-12 12:53:16.704389
Analysis finished2023-12-12 12:53:17.099895
Duration0.4 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

2021년_행정구역_시군구
Text

Distinct207
Distinct (%)90.4%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
2023-12-12T21:53:17.334524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length3
Mean length2.9519651
Min length2

Characters and Unicode

Total characters676
Distinct characters137
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

Unique200 ?
Unique (%)87.3%

Sample

1st row종로구
2nd row중구
3rd row용산구
4th row성동구
5th row광진구
ValueCountFrequency (%)
중구 6
 
2.6%
동구 6
 
2.6%
서구 5
 
2.2%
남구 4
 
1.7%
북구 4
 
1.7%
고성군 2
 
0.9%
강서구 2
 
0.9%
곡성군 1
 
0.4%
고흥군 1
 
0.4%
구미시 1
 
0.4%
Other values (197) 197
86.0%
2023-12-12T21:53:17.755272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
군 85
 
12.6%
시 79
 
11.7%
구 74
 
10.9%
천 22
 
3.3%
주 20
 
3.0%
양 18
 
2.7%
성 18
 
2.7%
동 17
 
2.5%
산 16
 
2.4%
서 13
 
1.9%
Other values (127) 314
46.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 676
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
군 85
 
12.6%
시 79
 
11.7%
구 74
 
10.9%
천 22
 
3.3%
주 20
 
3.0%
양 18
 
2.7%
성 18
 
2.7%
동 17
 
2.5%
산 16
 
2.4%
서 13
 
1.9%
Other values (127) 314
46.4%

Most occurring scripts

ValueCountFrequency (%)
Hangul 676
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
군 85
 
12.6%
시 79
 
11.7%
구 74
 
10.9%
천 22
 
3.3%
주 20
 
3.0%
양 18
 
2.7%
성 18
 
2.7%
동 17
 
2.5%
산 16
 
2.4%
서 13
 
1.9%
Other values (127) 314
46.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 676
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
군 85
 
12.6%
시 79
 
11.7%
구 74
 
10.9%
천 22
 
3.3%
주 20
 
3.0%
양 18
 
2.7%
성 18
 
2.7%
동 17
 
2.5%
산 16
 
2.4%
서 13
 
1.9%
Other values (127) 314
46.4%

부과(A)
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
0
229 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 229
100.0%

Length

2023-12-12T21:53:17.879843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:53:17.966333image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 229
100.0%

징수(B)
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
0
229 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 229
100.0%

Length

2023-12-12T21:53:18.056142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:53:18.150210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 229
100.0%

차이(A)-(B)
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
0
229 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 229
100.0%

Length

2023-12-12T21:53:18.225888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:53:18.299336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 229
100.0%

건수1
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
0
229 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 229
100.0%

Length

2023-12-12T21:53:18.401579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:53:18.482516image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 229
100.0%

금액1
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
0
229 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 229
100.0%

Length

2023-12-12T21:53:18.557882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:53:18.631892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 229
100.0%

건수2
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
0
229 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 229
100.0%

Length

2023-12-12T21:53:18.706920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:53:18.784111image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 229
100.0%

금액2
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
0
229 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 229
100.0%

Length

2023-12-12T21:53:18.874101image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:53:18.967508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 229
100.0%

징수율
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
0
229 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 229
100.0%

Length

2023-12-12T21:53:19.095814image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:53:19.200756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 229
100.0%

Missing values

2023-12-12T21:53:16.918267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T21:53:17.049269image/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

2021년_행정구역_시군구부과(A)징수(B)차이(A)-(B)건수1금액1건수2금액2징수율
0종로구00000000
1중구00000000
2용산구00000000
3성동구00000000
4광진구00000000
5동대문구00000000
6중랑구00000000
7성북구00000000
8강북구00000000
9도봉구00000000
2021년_행정구역_시군구부과(A)징수(B)차이(A)-(B)건수1금액1건수2금액2징수율
219횡성군00000000
220영월군00000000
221평창군00000000
222정선군00000000
223철원군00000000
224화천군00000000
225양구군00000000
226인제군00000000
227고성군00000000
228양양군00000000

Duplicate rows

Most frequently occurring

2021년_행정구역_시군구부과(A)징수(B)차이(A)-(B)건수1금액1건수2금액2징수율# duplicates
3동구000000006
6중구000000006
5서구000000005
2남구000000004
4북구000000004
0강서구000000002
1고성군000000002