Overview

Dataset statistics

Number of variables5
Number of observations95
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.9 KiB
Average record size in memory42.3 B

Variable types

Categorical1
Text3
Numeric1

Dataset

Description충청북도 보건지소 현황에 대한 데이터로서 충청북도 보건지소의 지소명, 전화번호, 우편번호, 주소 등의 정보를 제공합니다.
Author충청북도
URLhttps://www.data.go.kr/data/15071082/fileData.do

Alerts

우편번호 is highly overall correlated with 시군High correlation
시군 is highly overall correlated with 우편번호High correlation
전화번호 has unique valuesUnique
우편번호 has unique valuesUnique
주소 has unique valuesUnique

Reproduction

Analysis started2024-03-14 15:27:41.262464
Analysis finished2024-03-14 15:27:42.448090
Duration1.19 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군
Categorical

HIGH CORRELATION 

Distinct11
Distinct (%)11.6%
Missing0
Missing (%)0.0%
Memory size888.0 B
충청북도 청주시
14 
충청북도 충주시
13 
충청북도 괴산군
12 
충청북도 영동군
10 
충청북도 제천시
Other values (6)
38 

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique1 ?
Unique (%)1.1%

Sample

1st row충청북도 청주시
2nd row충청북도 청주시
3rd row충청북도 청주시
4th row충청북도 청주시
5th row충청북도 청주시

Common Values

ValueCountFrequency (%)
충청북도 청주시 14
14.7%
충청북도 충주시 13
13.7%
충청북도 괴산군 12
12.6%
충청북도 영동군 10
10.5%
충청북도 제천시 8
8.4%
충청북도 보은군 8
8.4%
충청북도 옥천군 8
8.4%
충청북도 음성군 8
8.4%
충청북도 단양군 7
7.4%
충청북도 진천군 6
6.3%

Length

2024-03-15T00:27:42.565075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
충청북도 95
50.0%
청주시 14
 
7.4%
충주시 13
 
6.8%
괴산군 12
 
6.3%
영동군 10
 
5.3%
제천시 8
 
4.2%
보은군 8
 
4.2%
옥천군 8
 
4.2%
음성군 8
 
4.2%
단양군 7
 
3.7%
Other values (2) 7
 
3.7%
Distinct94
Distinct (%)98.9%
Missing0
Missing (%)0.0%
Memory size888.0 B
2024-03-15T00:27:43.546737image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length2
Mean length2.1157895
Min length2

Characters and Unicode

Total characters201
Distinct characters99
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

Unique93 ?
Unique (%)97.9%

Sample

1st row낭성
2nd row미원
3rd row가덕
4th row문의
5th row남이
ValueCountFrequency (%)
덕산 2
 
2.1%
양산 1
 
1.1%
장연 1
 
1.1%
감물 1
 
1.1%
광혜원 1
 
1.1%
이월 1
 
1.1%
백곡 1
 
1.1%
문백 1
 
1.1%
초평 1
 
1.1%
도안 1
 
1.1%
Other values (84) 84
88.4%
2024-03-15T00:27:44.794732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
11
 
5.5%
8
 
4.0%
6
 
3.0%
5
 
2.5%
5
 
2.5%
5
 
2.5%
5
 
2.5%
5
 
2.5%
4
 
2.0%
4
 
2.0%
Other values (89) 143
71.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 201
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
11
 
5.5%
8
 
4.0%
6
 
3.0%
5
 
2.5%
5
 
2.5%
5
 
2.5%
5
 
2.5%
5
 
2.5%
4
 
2.0%
4
 
2.0%
Other values (89) 143
71.1%

Most occurring scripts

ValueCountFrequency (%)
Hangul 201
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
11
 
5.5%
8
 
4.0%
6
 
3.0%
5
 
2.5%
5
 
2.5%
5
 
2.5%
5
 
2.5%
5
 
2.5%
4
 
2.0%
4
 
2.0%
Other values (89) 143
71.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 201
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
11
 
5.5%
8
 
4.0%
6
 
3.0%
5
 
2.5%
5
 
2.5%
5
 
2.5%
5
 
2.5%
5
 
2.5%
4
 
2.0%
4
 
2.0%
Other values (89) 143
71.1%

전화번호
Text

UNIQUE 

Distinct95
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size888.0 B
2024-03-15T00:27:45.664587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters1140
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

Unique95 ?
Unique (%)100.0%

Sample

1st row043-201-3520
2nd row043-201-3530
3rd row043-201-3540
4th row043-201-3550
5th row043-201-3560
ValueCountFrequency (%)
043-201-3520 1
 
1.1%
043-833-1539 1
 
1.1%
043-832-7302 1
 
1.1%
043-833-9303 1
 
1.1%
043-539-7480 1
 
1.1%
043-539-7470 1
 
1.1%
043-539-7460 1
 
1.1%
043-539-7450 1
 
1.1%
043-539-7440 1
 
1.1%
043-539-7430 1
 
1.1%
Other values (85) 85
89.5%
2024-03-15T00:27:46.770882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 206
18.1%
3 195
17.1%
- 190
16.7%
4 169
14.8%
2 76
 
6.7%
5 60
 
5.3%
7 57
 
5.0%
8 54
 
4.7%
1 50
 
4.4%
9 46
 
4.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 950
83.3%
Dash Punctuation 190
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 206
21.7%
3 195
20.5%
4 169
17.8%
2 76
 
8.0%
5 60
 
6.3%
7 57
 
6.0%
8 54
 
5.7%
1 50
 
5.3%
9 46
 
4.8%
6 37
 
3.9%
Dash Punctuation
ValueCountFrequency (%)
- 190
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1140
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 206
18.1%
3 195
17.1%
- 190
16.7%
4 169
14.8%
2 76
 
6.7%
5 60
 
5.3%
7 57
 
5.0%
8 54
 
4.7%
1 50
 
4.4%
9 46
 
4.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1140
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 206
18.1%
3 195
17.1%
- 190
16.7%
4 169
14.8%
2 76
 
6.7%
5 60
 
5.3%
7 57
 
5.0%
8 54
 
4.7%
1 50
 
4.4%
9 46
 
4.0%

우편번호
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct95
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean28054.337
Minimum27006
Maximum29166
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size983.0 B
2024-03-15T00:27:47.023996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum27006
5-th percentile27023.8
Q127459.5
median28019
Q328905.5
95-th percentile29121.6
Maximum29166
Range2160
Interquartile range (IQR)1446

Descriptive statistics

Standard deviation702.06373
Coefficient of variation (CV)0.025025141
Kurtosis-1.1879337
Mean28054.337
Median Absolute Deviation (MAD)572
Skewness0.24558473
Sum2665162
Variance492893.48
MonotonicityNot monotonic
2024-03-15T00:27:47.273846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
28193 1
 
1.1%
28199 1
 
1.1%
28013 1
 
1.1%
28009 1
 
1.1%
28006 1
 
1.1%
27802 1
 
1.1%
27813 1
 
1.1%
27823 1
 
1.1%
27869 1
 
1.1%
27858 1
 
1.1%
Other values (85) 85
89.5%
ValueCountFrequency (%)
27006 1
1.1%
27014 1
1.1%
27015 1
1.1%
27018 1
1.1%
27021 1
1.1%
27025 1
1.1%
27027 1
1.1%
27105 1
1.1%
27114 1
1.1%
27123 1
1.1%
ValueCountFrequency (%)
29166 1
1.1%
29161 1
1.1%
29158 1
1.1%
29155 1
1.1%
29123 1
1.1%
29121 1
1.1%
29120 1
1.1%
29115 1
1.1%
29110 1
1.1%
29103 1
1.1%

주소
Text

UNIQUE 

Distinct95
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size888.0 B
2024-03-15T00:27:48.846749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length28
Mean length21.768421
Min length17

Characters and Unicode

Total characters2068
Distinct characters165
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

Unique95 ?
Unique (%)100.0%

Sample

1st row충청북도 청주시 상당구 낭성면 낭성시내길 27
2nd row충청북도 청주시 상당구 미원면 미원초정로 19-21
3rd row충청북도 청주시 상당구 가덕면 보청대로 4650
4th row충청북도 청주시 상당구 문의면 문의시내1길 12
5th row충청북도 청주시 서원구 남이면 척산길 7-12
ValueCountFrequency (%)
충청북도 95
 
19.5%
청주시 14
 
2.9%
충주시 13
 
2.7%
괴산군 12
 
2.5%
영동군 10
 
2.1%
옥천군 8
 
1.6%
음성군 8
 
1.6%
제천시 8
 
1.6%
보은군 7
 
1.4%
단양군 7
 
1.4%
Other values (274) 305
62.6%
2024-03-15T00:27:51.389697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
397
19.2%
122
 
5.9%
110
 
5.3%
98
 
4.7%
98
 
4.7%
85
 
4.1%
1 69
 
3.3%
67
 
3.2%
61
 
2.9%
44
 
2.1%
Other values (155) 917
44.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1357
65.6%
Space Separator 397
 
19.2%
Decimal Number 287
 
13.9%
Dash Punctuation 25
 
1.2%
Close Punctuation 1
 
< 0.1%
Open Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
122
 
9.0%
110
 
8.1%
98
 
7.2%
98
 
7.2%
85
 
6.3%
67
 
4.9%
61
 
4.5%
44
 
3.2%
39
 
2.9%
37
 
2.7%
Other values (141) 596
43.9%
Decimal Number
ValueCountFrequency (%)
1 69
24.0%
2 42
14.6%
3 31
10.8%
4 28
9.8%
9 24
 
8.4%
6 24
 
8.4%
5 23
 
8.0%
7 19
 
6.6%
8 14
 
4.9%
0 13
 
4.5%
Space Separator
ValueCountFrequency (%)
397
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 25
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1357
65.6%
Common 711
34.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
122
 
9.0%
110
 
8.1%
98
 
7.2%
98
 
7.2%
85
 
6.3%
67
 
4.9%
61
 
4.5%
44
 
3.2%
39
 
2.9%
37
 
2.7%
Other values (141) 596
43.9%
Common
ValueCountFrequency (%)
397
55.8%
1 69
 
9.7%
2 42
 
5.9%
3 31
 
4.4%
4 28
 
3.9%
- 25
 
3.5%
9 24
 
3.4%
6 24
 
3.4%
5 23
 
3.2%
7 19
 
2.7%
Other values (4) 29
 
4.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1357
65.6%
ASCII 711
34.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
397
55.8%
1 69
 
9.7%
2 42
 
5.9%
3 31
 
4.4%
4 28
 
3.9%
- 25
 
3.5%
9 24
 
3.4%
6 24
 
3.4%
5 23
 
3.2%
7 19
 
2.7%
Other values (4) 29
 
4.1%
Hangul
ValueCountFrequency (%)
122
 
9.0%
110
 
8.1%
98
 
7.2%
98
 
7.2%
85
 
6.3%
67
 
4.9%
61
 
4.5%
44
 
3.2%
39
 
2.9%
37
 
2.7%
Other values (141) 596
43.9%

Interactions

2024-03-15T00:27:41.706381image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-15T00:27:51.719170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군지소명전화번호우편번호주소
시군1.0000.9021.0000.9321.000
지소명0.9021.0001.0000.8751.000
전화번호1.0001.0001.0001.0001.000
우편번호0.9320.8751.0001.0001.000
주소1.0001.0001.0001.0001.000
2024-03-15T00:27:52.028936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
우편번호시군
우편번호1.0000.778
시군0.7781.000

Missing values

2024-03-15T00:27:42.016623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-15T00:27:42.327657image/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

시군지소명전화번호우편번호주소
0충청북도 청주시낭성043-201-352028193충청북도 청주시 상당구 낭성면 낭성시내길 27
1충청북도 청주시미원043-201-353028199충청북도 청주시 상당구 미원면 미원초정로 19-21
2충청북도 청주시가덕043-201-354028203충청북도 청주시 상당구 가덕면 보청대로 4650
3충청북도 청주시문의043-201-355028208충청북도 청주시 상당구 문의면 문의시내1길 12
4충청북도 청주시남이043-201-356028182충청북도 청주시 서원구 남이면 척산길 7-12
5충청북도 청주시현도043-201-357028215충청북도 청주시 서원구 현도면 선동1길 10
6충청북도 청주시오송043-201-360028168충청북도 청주시 흥덕구 오송읍 가로수로 174
7충청북도 청주시오송생명043-201-361028265충청북도 청주시 흥덕구 오송읍 오송생명3로 67
8충청북도 청주시강내043-201-362028172충청북도 청주시 흥덕구 강내면 태성탑연로 433
9충청북도 청주시옥산043-201-363028113충청북도 청주시 흥덕구 옥산면 옥산시내1길 45-9
시군지소명전화번호우편번호주소
85충청북도 음성군삼성043-871-297027652충청북도 음성군 삼성면 덕정로 30번길 8
86충청북도 음성군생극043-871-298027619충청북도 음성군 생극면 음성로1626번길 19
87충청북도 음성군감곡043-882-969627604충청북도 음성군 감곡면 장감로 124번길 15
88충청북도 단양군매포043-420-328427006충청북도 단양군 매포읍 평동33길 3
89충청북도 단양군단성043-420-328827025충청북도 단양군 단성면 충혼로 52-1
90충청북도 단양군대강043-420-329427027충청북도 단양군 대강면 단양로176
91충청북도 단양군가곡043-420-329727021충청북도 단양군 가곡면 사평4길 11-4
92충청북도 단양군영춘043-420-337527018충청북도 단양군 영춘면 온달평강로 39
93충청북도 단양군어상천043-420-335927015충청북도 단양군 어상천면 매포어상천로 1257-16
94충청북도 단양군적성043-420-336427014충청북도 단양군 적성면 하리 금수산로 957-2