Overview

Dataset statistics

Number of variables6
Number of observations35
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.8 KiB
Average record size in memory52.8 B

Variable types

Categorical1
Text3
Numeric1
DateTime1

Dataset

Description관공서 현황(주소, 전화번호)
Author경기도 용인시
URLhttps://www.data.go.kr/data/15046175/fileData.do

Alerts

시군명 has constant value ""Constant
데이터기준일자 has constant value ""Constant
구분명 has unique valuesUnique
Unnamed: 2 has unique valuesUnique
우편번호 has unique valuesUnique
전화번호안내 has unique valuesUnique

Reproduction

Analysis started2023-12-12 18:26:54.022942
Analysis finished2023-12-12 18:26:54.603335
Duration0.58 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군명
Categorical

CONSTANT 

Distinct1
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size412.0 B
용인시
35 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
용인시 35
100.0%

Length

2023-12-13T03:26:54.771686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T03:26:54.935624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
용인시 35
100.0%

구분명
Text

UNIQUE 

Distinct35
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size412.0 B
2023-12-13T03:26:55.189578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
Mean length3.3428571
Min length3

Characters and Unicode

Total characters117
Distinct characters52
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

Unique35 ?
Unique (%)100.0%

Sample

1st row용인시청
2nd row처인구청
3rd row포곡읍
4th row모현면
5th row남사면
ValueCountFrequency (%)
용인시청 1
 
2.9%
기흥동 1
 
2.9%
구성동 1
 
2.9%
마북동 1
 
2.9%
동백동 1
 
2.9%
상하동 1
 
2.9%
보정동 1
 
2.9%
수지구청 1
 
2.9%
서농동 1
 
2.9%
풍덕천1동 1
 
2.9%
Other values (25) 25
71.4%
2023-12-13T03:26:55.715861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 28
23.9%
면 6
 
5.1%
구 5
 
4.3%
청 4
 
3.4%
상 4
 
3.4%
덕 3
 
2.6%
2 3
 
2.6%
1 3
 
2.6%
천 3
 
2.6%
현 3
 
2.6%
Other values (42) 55
47.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 111
94.9%
Decimal Number 6
 
5.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 28
25.2%
면 6
 
5.4%
구 5
 
4.5%
청 4
 
3.6%
상 4
 
3.6%
덕 3
 
2.7%
천 3
 
2.7%
현 3
 
2.7%
갈 3
 
2.7%
인 2
 
1.8%
Other values (40) 50
45.0%
Decimal Number
ValueCountFrequency (%)
2 3
50.0%
1 3
50.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 111
94.9%
Common 6
 
5.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 28
25.2%
면 6
 
5.4%
구 5
 
4.5%
청 4
 
3.6%
상 4
 
3.6%
덕 3
 
2.7%
천 3
 
2.7%
현 3
 
2.7%
갈 3
 
2.7%
인 2
 
1.8%
Other values (40) 50
45.0%
Common
ValueCountFrequency (%)
2 3
50.0%
1 3
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 111
94.9%
ASCII 6
 
5.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 28
25.2%
면 6
 
5.4%
구 5
 
4.5%
청 4
 
3.6%
상 4
 
3.6%
덕 3
 
2.7%
천 3
 
2.7%
현 3
 
2.7%
갈 3
 
2.7%
인 2
 
1.8%
Other values (40) 50
45.0%
ASCII
ValueCountFrequency (%)
2 3
50.0%
1 3
50.0%

Unnamed: 2
Text

UNIQUE 

Distinct35
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size412.0 B
2023-12-13T03:26:55.995252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length31
Median length28
Mean length25.942857
Min length22

Characters and Unicode

Total characters908
Distinct characters98
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

Unique35 ?
Unique (%)100.0%

Sample

1st row경기도 용인시 처인구 중부대로 1199(삼가동)
2nd row경기도 용인시 처인구 금령로 50(김량장동)
3rd row경기도 용인시 처인구 포곡읍 포곡로 258(삼계리)
4th row경기도 용인시 처인구 모현면 독점로 31-6(갈담리)
5th row경기도 용인시 처인구 남사면 내기로 22(봉무리)
ValueCountFrequency (%)
경기도 35
19.2%
용인시 35
19.2%
처인구 13
 
7.1%
기흥구 12
 
6.6%
수지구 10
 
5.5%
포은대로 2
 
1.1%
중부대로 2
 
1.1%
만현로 1
 
0.5%
구성로77번길 1
 
0.5%
어정로 1
 
0.5%
Other values (70) 70
38.5%
2023-12-13T03:26:56.436940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
147
 
16.2%
기 49
 
5.4%
인 48
 
5.3%
구 39
 
4.3%
경 36
 
4.0%
( 35
 
3.9%
로 35
 
3.9%
) 35
 
3.9%
도 35
 
3.9%
시 35
 
3.9%
Other values (88) 414
45.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 579
63.8%
Space Separator 147
 
16.2%
Decimal Number 109
 
12.0%
Open Punctuation 35
 
3.9%
Close Punctuation 35
 
3.9%
Dash Punctuation 3
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
기 49
 
8.5%
인 48
 
8.3%
구 39
 
6.7%
경 36
 
6.2%
로 35
 
6.0%
도 35
 
6.0%
시 35
 
6.0%
용 35
 
6.0%
동 34
 
5.9%
지 17
 
2.9%
Other values (74) 216
37.3%
Decimal Number
ValueCountFrequency (%)
1 26
23.9%
5 15
13.8%
3 13
11.9%
2 12
11.0%
4 10
 
9.2%
7 9
 
8.3%
8 7
 
6.4%
6 6
 
5.5%
0 6
 
5.5%
9 5
 
4.6%
Space Separator
ValueCountFrequency (%)
147
100.0%
Open Punctuation
ValueCountFrequency (%)
( 35
100.0%
Close Punctuation
ValueCountFrequency (%)
) 35
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 579
63.8%
Common 329
36.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
기 49
 
8.5%
인 48
 
8.3%
구 39
 
6.7%
경 36
 
6.2%
로 35
 
6.0%
도 35
 
6.0%
시 35
 
6.0%
용 35
 
6.0%
동 34
 
5.9%
지 17
 
2.9%
Other values (74) 216
37.3%
Common
ValueCountFrequency (%)
147
44.7%
( 35
 
10.6%
) 35
 
10.6%
1 26
 
7.9%
5 15
 
4.6%
3 13
 
4.0%
2 12
 
3.6%
4 10
 
3.0%
7 9
 
2.7%
8 7
 
2.1%
Other values (4) 20
 
6.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 579
63.8%
ASCII 329
36.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
147
44.7%
( 35
 
10.6%
) 35
 
10.6%
1 26
 
7.9%
5 15
 
4.6%
3 13
 
4.0%
2 12
 
3.6%
4 10
 
3.0%
7 9
 
2.7%
8 7
 
2.1%
Other values (4) 20
 
6.1%
Hangul
ValueCountFrequency (%)
기 49
 
8.5%
인 48
 
8.3%
구 39
 
6.7%
경 36
 
6.2%
로 35
 
6.0%
도 35
 
6.0%
시 35
 
6.0%
용 35
 
6.0%
동 34
 
5.9%
지 17
 
2.9%
Other values (74) 216
37.3%

우편번호
Real number (ℝ)

UNIQUE 

Distinct35
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean16990.8
Minimum16825
Maximum17178
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size447.0 B
2023-12-13T03:26:56.632442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum16825
5-th percentile16834.1
Q116904
median16994
Q317063.5
95-th percentile17161
Maximum17178
Range353
Interquartile range (IQR)159.5

Descriptive statistics

Standard deviation108.53864
Coefficient of variation (CV)0.0063880827
Kurtosis-1.1418384
Mean16990.8
Median Absolute Deviation (MAD)84
Skewness0.062502183
Sum594678
Variance11780.635
MonotonicityNot monotonic
2023-12-13T03:26:57.132719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=35)
ValueCountFrequency (%)
17019 1
 
2.9%
17049 1
 
2.9%
16917 1
 
2.9%
16910 1
 
2.9%
17007 1
 
2.9%
16994 1
 
2.9%
16898 1
 
2.9%
16835 1
 
2.9%
16832 1
 
2.9%
16844 1
 
2.9%
Other values (25) 25
71.4%
ValueCountFrequency (%)
16825 1
2.9%
16832 1
2.9%
16835 1
2.9%
16844 1
2.9%
16845 1
2.9%
16852 1
2.9%
16870 1
2.9%
16872 1
2.9%
16898 1
2.9%
16910 1
2.9%
ValueCountFrequency (%)
17178 1
2.9%
17168 1
2.9%
17158 1
2.9%
17144 1
2.9%
17136 1
2.9%
17118 1
2.9%
17108 1
2.9%
17085 1
2.9%
17072 1
2.9%
17055 1
2.9%

전화번호안내
Text

UNIQUE 

Distinct35
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size412.0 B
2023-12-13T03:26:57.413321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length11.914286
Min length9

Characters and Unicode

Total characters417
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique35 ?
Unique (%)100.0%

Sample

1st row1577-1122
2nd row031-324-5023
3rd row031-324-5531
4th row031-324-5592
5th row031-324-5641
ValueCountFrequency (%)
1577-1122 1
 
2.9%
031-324-6678 1
 
2.9%
031-324-6717 1
 
2.9%
031-324-6732 1
 
2.9%
031-324-6893 1
 
2.9%
031-324-6795 1
 
2.9%
031-324-6772 1
 
2.9%
031-324-8021 1
 
2.9%
031-324-6681 1
 
2.9%
031-324-8602 1
 
2.9%
Other values (25) 25
71.4%
2023-12-13T03:26:57.856811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 79
18.9%
- 69
16.5%
2 54
12.9%
1 47
11.3%
4 41
9.8%
0 40
9.6%
6 27
 
6.5%
5 18
 
4.3%
7 16
 
3.8%
8 16
 
3.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 348
83.5%
Dash Punctuation 69
 
16.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 79
22.7%
2 54
15.5%
1 47
13.5%
4 41
11.8%
0 40
11.5%
6 27
 
7.8%
5 18
 
5.2%
7 16
 
4.6%
8 16
 
4.6%
9 10
 
2.9%
Dash Punctuation
ValueCountFrequency (%)
- 69
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 417
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
3 79
18.9%
- 69
16.5%
2 54
12.9%
1 47
11.3%
4 41
9.8%
0 40
9.6%
6 27
 
6.5%
5 18
 
4.3%
7 16
 
3.8%
8 16
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 417
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 79
18.9%
- 69
16.5%
2 54
12.9%
1 47
11.3%
4 41
9.8%
0 40
9.6%
6 27
 
6.5%
5 18
 
4.3%
7 16
 
3.8%
8 16
 
3.8%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size412.0 B
Minimum2016-02-24 00:00:00
Maximum2016-02-24 00:00:00
2023-12-13T03:26:57.958848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:26:58.047257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-13T03:26:54.232018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T03:26:58.113422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분명Unnamed: 2우편번호전화번호안내
구분명1.0001.0001.0001.000
Unnamed: 21.0001.0001.0001.000
우편번호1.0001.0001.0001.000
전화번호안내1.0001.0001.0001.000

Missing values

2023-12-13T03:26:54.378198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T03:26:54.546313image/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

시군명구분명Unnamed: 2우편번호전화번호안내데이터기준일자
0용인시용인시청경기도 용인시 처인구 중부대로 1199(삼가동)170191577-11222016-02-24
1용인시처인구청경기도 용인시 처인구 금령로 50(김량장동)17049031-324-50232016-02-24
2용인시포곡읍경기도 용인시 처인구 포곡읍 포곡로 258(삼계리)17028031-324-55312016-02-24
3용인시모현면경기도 용인시 처인구 모현면 독점로 31-6(갈담리)17036031-324-55922016-02-24
4용인시남사면경기도 용인시 처인구 남사면 내기로 22(봉무리)17118031-324-56412016-02-24
5용인시이동면경기도 용인시 처인구 이동면 경기동로 673(송전리)17136031-324-56912016-02-24
6용인시원삼면경기도 용인시 처인구 원삼면 원양로 64(고당리)17168031-324-57422016-02-24
7용인시백암면경기도 용인시 처인구 백암면 백암로 189(백암리)17178031-324-57922016-02-24
8용인시양지면경기도 용인시 처인구 양지면 양지로105번길 5(양지리)17158031-324-58422016-02-24
9용인시중앙동경기도 용인시 처인구 금령로78번길 7(김량장동)17051031-324-58942016-02-24
시군명구분명Unnamed: 2우편번호전화번호안내데이터기준일자
25용인시수지구청경기도 용인시 수지구 포은대로 435(풍덕천동)16835031-324-80212016-02-24
26용인시풍덕천1동경기도 용인시 수지구 수지로342번길 3(풍덕천동)16832031-324-86022016-02-24
27용인시풍덕천2동경기도 용인시 수지구 풍덕천로 51(풍덕천동)16844031-324-86332016-02-24
28용인시신봉동경기도 용인시 수지구 수지로 215(신봉동)16845031-324-86422016-02-24
29용인시죽전1동경기도 용인시 수지구 대지로15번길 50(죽전동)16872031-324-86622016-02-24
30용인시죽전2동경기도 용인시 수지구 포은대로 523(죽전동)16870031-264-66932016-02-24
31용인시동천동경기도 용인시 수지구 신수로783번길 40(동천동)16825031-324-87022016-02-24
32용인시상현1동경기도 용인시 수지구 상현로 71(상현동)16937031-324-87332016-02-24
33용인시상현2동경기도 용인시 수지구 만현로 48(상현동)16929031-324-87522016-02-24
34용인시성복동경기도 용인시 수지구 성복1로 100(성복동)16852031-324-87722016-02-24