Overview

Dataset statistics

Number of variables10
Number of observations403
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory32.4 KiB
Average record size in memory82.3 B

Variable types

Numeric1
Categorical6
Text3

Alerts

자료출처 has constant value ""Constant
공개여부 has constant value ""Constant
작성일 has constant value ""Constant
갱신주기 has constant value ""Constant
순번 is highly overall correlated with 시군명 and 1 other fieldsHigh correlation
시군명 is highly overall correlated with 순번High correlation
분류 is highly overall correlated with 순번High correlation
순번 has unique valuesUnique

Reproduction

Analysis started2024-03-14 01:20:42.808320
Analysis finished2024-03-14 01:20:43.374193
Duration0.57 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct403
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean202
Minimum1
Maximum403
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.7 KiB
2024-03-14T10:20:43.436440image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile21.1
Q1101.5
median202
Q3302.5
95-th percentile382.9
Maximum403
Range402
Interquartile range (IQR)201

Descriptive statistics

Standard deviation116.48033
Coefficient of variation (CV)0.57663528
Kurtosis-1.2
Mean202
Median Absolute Deviation (MAD)101
Skewness0
Sum81406
Variance13567.667
MonotonicityStrictly increasing
2024-03-14T10:20:43.554301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.2%
267 1
 
0.2%
277 1
 
0.2%
276 1
 
0.2%
275 1
 
0.2%
274 1
 
0.2%
273 1
 
0.2%
272 1
 
0.2%
271 1
 
0.2%
270 1
 
0.2%
Other values (393) 393
97.5%
ValueCountFrequency (%)
1 1
0.2%
2 1
0.2%
3 1
0.2%
4 1
0.2%
5 1
0.2%
6 1
0.2%
7 1
0.2%
8 1
0.2%
9 1
0.2%
10 1
0.2%
ValueCountFrequency (%)
403 1
0.2%
402 1
0.2%
401 1
0.2%
400 1
0.2%
399 1
0.2%
398 1
0.2%
397 1
0.2%
396 1
0.2%
395 1
0.2%
394 1
0.2%

시군명
Categorical

HIGH CORRELATION 

Distinct14
Distinct (%)3.5%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
정읍시
42 
익산시
40 
남원시
40 
김제시
40 
군산시
34 
Other values (9)
207 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row전주시
2nd row군산시
3rd row익산시
4th row정읍시
5th row남원시

Common Values

ValueCountFrequency (%)
정읍시 42
10.4%
익산시 40
9.9%
남원시 40
9.9%
김제시 40
9.9%
군산시 34
8.4%
고창군 34
8.4%
임실군 32
7.9%
완주군 30
7.4%
순창군 28
6.9%
진안군 23
 
5.7%
Other values (4) 60
14.9%

Length

2024-03-14T10:20:43.660336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
정읍시 42
10.4%
익산시 40
9.9%
남원시 40
9.9%
김제시 40
9.9%
군산시 34
8.4%
고창군 34
8.4%
임실군 32
7.9%
완주군 30
7.4%
순창군 28
6.9%
진안군 23
 
5.7%
Other values (4) 60
14.9%

분류
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
보건진료소
240 
보건지소
149 
보건소
 
14

Length

Max length5
Median length5
Mean length4.560794
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
보건진료소 240
59.6%
보건지소 149
37.0%
보건소 14
 
3.5%

Length

2024-03-14T10:20:43.756242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T10:20:43.884807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
보건진료소 240
59.6%
보건지소 149
37.0%
보건소 14
 
3.5%

보건소명
Text

Distinct392
Distinct (%)97.3%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
2024-03-14T10:20:44.133547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length7
Mean length6.7816377
Min length6

Characters and Unicode

Total characters2733
Distinct characters187
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

Unique383 ?
Unique (%)95.0%

Sample

1st row전주시보건소
2nd row군산시보건소
3rd row익산시보건소
4th row정읍시보건소
5th row남원시보건소
ValueCountFrequency (%)
성덕보건진료소 3
 
0.7%
성동보건진료소 3
 
0.7%
하제보건진료소 2
 
0.5%
금평보건진료소 2
 
0.5%
대곡보건진료소 2
 
0.5%
성수보건지소 2
 
0.5%
대산면보건지소 2
 
0.5%
학선보건진료소 2
 
0.5%
회룡보건진료소 2
 
0.5%
돈지보건진료소 1
 
0.2%
Other values (382) 382
94.8%
2024-03-14T10:20:44.518714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
보 406
14.9%
건 404
14.8%
소 403
14.7%
진 250
 
9.1%
료 244
 
8.9%
지 160
 
5.9%
산 49
 
1.8%
면 36
 
1.3%
동 28
 
1.0%
성 24
 
0.9%
Other values (177) 729
26.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2733
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
보 406
14.9%
건 404
14.8%
소 403
14.7%
진 250
 
9.1%
료 244
 
8.9%
지 160
 
5.9%
산 49
 
1.8%
면 36
 
1.3%
동 28
 
1.0%
성 24
 
0.9%
Other values (177) 729
26.7%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2733
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
보 406
14.9%
건 404
14.8%
소 403
14.7%
진 250
 
9.1%
료 244
 
8.9%
지 160
 
5.9%
산 49
 
1.8%
면 36
 
1.3%
동 28
 
1.0%
성 24
 
0.9%
Other values (177) 729
26.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2733
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
보 406
14.9%
건 404
14.8%
소 403
14.7%
진 250
 
9.1%
료 244
 
8.9%
지 160
 
5.9%
산 49
 
1.8%
면 36
 
1.3%
동 28
 
1.0%
성 24
 
0.9%
Other values (177) 729
26.7%

도로명주소
Text

Distinct402
Distinct (%)99.8%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
2024-03-14T10:20:44.852257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length19
Mean length15.362283
Min length10

Characters and Unicode

Total characters6191
Distinct characters243
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

Unique401 ?
Unique (%)99.5%

Sample

1st row전주시 완산구 전라감영로 33
2nd row군산시 수송동로 58
3rd row익산시 무왕로 975
4th row정읍시 수성1로 61
5th row남원시 요천로 1285
ValueCountFrequency (%)
정읍시 42
 
2.6%
김제시 40
 
2.5%
익산시 40
 
2.5%
남원시 40
 
2.5%
고창군 34
 
2.1%
군산시 34
 
2.1%
임실군 32
 
2.0%
완주군 30
 
1.9%
순창군 28
 
1.8%
진안군 23
 
1.4%
Other values (835) 1257
78.6%
2024-03-14T10:20:45.288459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1197
 
19.3%
면 358
 
5.8%
1 259
 
4.2%
군 238
 
3.8%
시 204
 
3.3%
길 203
 
3.3%
로 201
 
3.2%
산 160
 
2.6%
2 152
 
2.5%
3 144
 
2.3%
Other values (233) 3075
49.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3725
60.2%
Space Separator 1197
 
19.3%
Decimal Number 1175
 
19.0%
Dash Punctuation 94
 
1.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
면 358
 
9.6%
군 238
 
6.4%
시 204
 
5.5%
길 203
 
5.4%
로 201
 
5.4%
산 160
 
4.3%
안 74
 
2.0%
창 73
 
2.0%
읍 73
 
2.0%
주 71
 
1.9%
Other values (221) 2070
55.6%
Decimal Number
ValueCountFrequency (%)
1 259
22.0%
2 152
12.9%
3 144
12.3%
4 115
9.8%
8 102
 
8.7%
5 97
 
8.3%
6 93
 
7.9%
0 75
 
6.4%
9 73
 
6.2%
7 65
 
5.5%
Space Separator
ValueCountFrequency (%)
1197
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 94
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3725
60.2%
Common 2466
39.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
면 358
 
9.6%
군 238
 
6.4%
시 204
 
5.5%
길 203
 
5.4%
로 201
 
5.4%
산 160
 
4.3%
안 74
 
2.0%
창 73
 
2.0%
읍 73
 
2.0%
주 71
 
1.9%
Other values (221) 2070
55.6%
Common
ValueCountFrequency (%)
1197
48.5%
1 259
 
10.5%
2 152
 
6.2%
3 144
 
5.8%
4 115
 
4.7%
8 102
 
4.1%
5 97
 
3.9%
- 94
 
3.8%
6 93
 
3.8%
0 75
 
3.0%
Other values (2) 138
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3725
60.2%
ASCII 2466
39.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1197
48.5%
1 259
 
10.5%
2 152
 
6.2%
3 144
 
5.8%
4 115
 
4.7%
8 102
 
4.1%
5 97
 
3.9%
- 94
 
3.8%
6 93
 
3.8%
0 75
 
3.0%
Other values (2) 138
 
5.6%
Hangul
ValueCountFrequency (%)
면 358
 
9.6%
군 238
 
6.4%
시 204
 
5.5%
길 203
 
5.4%
로 201
 
5.4%
산 160
 
4.3%
안 74
 
2.0%
창 73
 
2.0%
읍 73
 
2.0%
주 71
 
1.9%
Other values (221) 2070
55.6%

전화번호
Text

Distinct399
Distinct (%)99.0%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
2024-03-14T10:20:45.508207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length11.992556
Min length9

Characters and Unicode

Total characters4833
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

Unique395 ?
Unique (%)98.0%

Sample

1st row063-281-6200
2nd row063-463-4000
3rd row1577-0072
4th row063-539-6137
5th row063-625-4000
ValueCountFrequency (%)
063-538-8368 2
 
0.5%
063-571-2017 2
 
0.5%
063-290-3131 2
 
0.5%
063-320-8314 2
 
0.5%
063-583-3332 1
 
0.2%
063-583-6359 1
 
0.2%
063-582-1920 1
 
0.2%
063-583-5679 1
 
0.2%
063-582-3654 1
 
0.2%
063-582-1184 1
 
0.2%
Other values (389) 389
96.5%
2024-03-14T10:20:45.806448image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 805
16.7%
0 737
15.2%
6 706
14.6%
3 705
14.6%
5 419
8.7%
4 350
7.2%
8 279
 
5.8%
2 273
 
5.6%
9 204
 
4.2%
7 179
 
3.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4028
83.3%
Dash Punctuation 805
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 737
18.3%
6 706
17.5%
3 705
17.5%
5 419
10.4%
4 350
8.7%
8 279
 
6.9%
2 273
 
6.8%
9 204
 
5.1%
7 179
 
4.4%
1 176
 
4.4%
Dash Punctuation
ValueCountFrequency (%)
- 805
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4833
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 805
16.7%
0 737
15.2%
6 706
14.6%
3 705
14.6%
5 419
8.7%
4 350
7.2%
8 279
 
5.8%
2 273
 
5.6%
9 204
 
4.2%
7 179
 
3.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4833
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 805
16.7%
0 737
15.2%
6 706
14.6%
3 705
14.6%
5 419
8.7%
4 350
7.2%
8 279
 
5.8%
2 273
 
5.6%
9 204
 
4.2%
7 179
 
3.7%

자료출처
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
보건의료과
403 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
보건의료과 403
100.0%

Length

2024-03-14T10:20:45.919748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T10:20:45.989206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
보건의료과 403
100.0%

공개여부
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
공개
403 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
공개 403
100.0%

Length

2024-03-14T10:20:46.064778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T10:20:46.167699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
공개 403
100.0%

작성일
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
2015.1
403 

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2015.1
2nd row2015.1
3rd row2015.1
4th row2015.1
5th row2015.1

Common Values

ValueCountFrequency (%)
2015.1 403
100.0%

Length

2024-03-14T10:20:46.283006image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T10:20:46.376574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2015.1 403
100.0%

갱신주기
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
1년
403 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1년
2nd row1년
3rd row1년
4th row1년
5th row1년

Common Values

ValueCountFrequency (%)
1년 403
100.0%

Length

2024-03-14T10:20:46.461441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T10:20:46.540918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1년 403
100.0%

Interactions

2024-03-14T10:20:43.114457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-14T10:20:46.586341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번시군명분류
순번1.0000.8700.862
시군명0.8701.0000.000
분류0.8620.0001.000
2024-03-14T10:20:46.654595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군명분류
시군명1.0000.000
분류0.0001.000
2024-03-14T10:20:46.720251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번시군명분류
순번1.0000.5940.781
시군명0.5941.0000.000
분류0.7810.0001.000

Missing values

2024-03-14T10:20:43.229181image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T10:20:43.331907image/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

순번시군명분류보건소명도로명주소전화번호자료출처공개여부작성일갱신주기
01전주시보건소전주시보건소전주시 완산구 전라감영로 33063-281-6200보건의료과공개2015.11년
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