Overview

Dataset statistics

Number of variables12
Number of observations34
Missing cells58
Missing cells (%)14.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.5 KiB
Average record size in memory106.9 B

Variable types

Text4
Numeric7
Categorical1

Alerts

영업상태명 has constant value ""Constant
소재지우편번호 is highly overall correlated with WGS84위도High correlation
자격소유인원수(명) is highly overall correlated with 총인원수(명)High correlation
총인원수(명) is highly overall correlated with 자격소유인원수(명)High correlation
WGS84위도 is highly overall correlated with 소재지우편번호High correlation
소재지우편번호 has 12 (35.3%) missing valuesMissing
소재지도로명주소 has 17 (50.0%) missing valuesMissing
입소정원(명) has 1 (2.9%) missing valuesMissing
WGS84위도 has 14 (41.2%) missing valuesMissing
WGS84경도 has 14 (41.2%) missing valuesMissing
소재지지번주소 has unique valuesUnique
입소정원(명) has 22 (64.7%) zerosZeros
자격소유인원수(명) has 7 (20.6%) zerosZeros
총인원수(명) has 4 (11.8%) zerosZeros

Reproduction

Analysis started2023-12-10 22:06:24.731598
Analysis finished2023-12-10 22:06:29.525136
Duration4.79 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군명
Text

Distinct25
Distinct (%)73.5%
Missing0
Missing (%)0.0%
Memory size404.0 B
2023-12-11T07:06:29.637558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length3
Mean length3.0882353
Min length3

Characters and Unicode

Total characters105
Distinct characters30
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

Unique17 ?
Unique (%)50.0%

Sample

1st row고양시
2nd row광명시
3rd row광주시
4th row구리시
5th row군포시
ValueCountFrequency (%)
부천시 3
 
8.8%
성남시 2
 
5.9%
시흥시 2
 
5.9%
안산시 2
 
5.9%
안성시 2
 
5.9%
의정부시 2
 
5.9%
김포시 2
 
5.9%
파주시 2
 
5.9%
평택시 1
 
2.9%
고양시 1
 
2.9%
Other values (15) 15
44.1%
2023-12-11T07:06:29.906175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
시 35
33.3%
주 6
 
5.7%
부 5
 
4.8%
성 5
 
4.8%
양 5
 
4.8%
안 5
 
4.8%
천 5
 
4.8%
포 4
 
3.8%
남 4
 
3.8%
산 3
 
2.9%
Other values (20) 28
26.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 105
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 35
33.3%
주 6
 
5.7%
부 5
 
4.8%
성 5
 
4.8%
양 5
 
4.8%
안 5
 
4.8%
천 5
 
4.8%
포 4
 
3.8%
남 4
 
3.8%
산 3
 
2.9%
Other values (20) 28
26.7%

Most occurring scripts

ValueCountFrequency (%)
Hangul 105
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 35
33.3%
주 6
 
5.7%
부 5
 
4.8%
성 5
 
4.8%
양 5
 
4.8%
안 5
 
4.8%
천 5
 
4.8%
포 4
 
3.8%
남 4
 
3.8%
산 3
 
2.9%
Other values (20) 28
26.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 105
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
시 35
33.3%
주 6
 
5.7%
부 5
 
4.8%
성 5
 
4.8%
양 5
 
4.8%
안 5
 
4.8%
천 5
 
4.8%
포 4
 
3.8%
남 4
 
3.8%
산 3
 
2.9%
Other values (20) 28
26.7%

사업장명
Text

Distinct33
Distinct (%)97.1%
Missing0
Missing (%)0.0%
Memory size404.0 B
2023-12-11T07:06:30.111343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length12
Mean length9.3529412
Min length6

Characters and Unicode

Total characters318
Distinct characters57
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

Unique32 ?
Unique (%)94.1%

Sample

1st row고양지역자활센터
2nd row경기광명지역자활센터
3rd row경기광주 지역자활센터
4th row구리지역자활센터
5th row군포지역자활센터
ValueCountFrequency (%)
경기김포지역자활센터 2
 
5.7%
이천지역자활센터 1
 
2.9%
하남지역자활센터 1
 
2.9%
포천지역자활센터 1
 
2.9%
평택지역자활센터 1
 
2.9%
파주지역자활 1
 
2.9%
파주지역자활센터 1
 
2.9%
안성지역자활센터 1
 
2.9%
의정부지역자활센터 1
 
2.9%
안성맞춤지역자활센터 1
 
2.9%
Other values (24) 24
68.6%
2023-12-11T07:06:30.471911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
지 35
11.0%
자 34
10.7%
역 33
 
10.4%
활 33
 
10.4%
센 32
 
10.1%
터 32
 
10.1%
경 12
 
3.8%
기 12
 
3.8%
주 6
 
1.9%
양 6
 
1.9%
Other values (47) 83
26.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 317
99.7%
Space Separator 1
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
지 35
11.0%
자 34
10.7%
역 33
10.4%
활 33
10.4%
센 32
 
10.1%
터 32
 
10.1%
경 12
 
3.8%
기 12
 
3.8%
주 6
 
1.9%
양 6
 
1.9%
Other values (46) 82
25.9%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 317
99.7%
Common 1
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
지 35
11.0%
자 34
10.7%
역 33
10.4%
활 33
10.4%
센 32
 
10.1%
터 32
 
10.1%
경 12
 
3.8%
기 12
 
3.8%
주 6
 
1.9%
양 6
 
1.9%
Other values (46) 82
25.9%
Common
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 317
99.7%
ASCII 1
 
0.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
지 35
11.0%
자 34
10.7%
역 33
10.4%
활 33
10.4%
센 32
 
10.1%
터 32
 
10.1%
경 12
 
3.8%
기 12
 
3.8%
주 6
 
1.9%
양 6
 
1.9%
Other values (46) 82
25.9%
ASCII
ValueCountFrequency (%)
1
100.0%

소재지우편번호
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct22
Distinct (%)100.0%
Missing12
Missing (%)35.3%
Infinite0
Infinite (%)0.0%
Mean13641
Minimum10017
Maximum18122
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size438.0 B
2023-12-11T07:06:30.580537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10017
5-th percentile10922.4
Q111683
median13604.5
Q314960.75
95-th percentile17862.3
Maximum18122
Range8105
Interquartile range (IQR)3277.75

Descriptive statistics

Standard deviation2386.6033
Coefficient of variation (CV)0.17495809
Kurtosis-0.7598355
Mean13641
Median Absolute Deviation (MAD)1887.5
Skewness0.43494544
Sum300102
Variance5695875.4
MonotonicityNot monotonic
2023-12-11T07:06:30.690729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
17583 1
 
2.9%
11150 1
 
2.9%
17877 1
 
2.9%
10930 1
 
2.9%
10922 1
 
2.9%
11719 1
 
2.9%
11671 1
 
2.9%
18122 1
 
2.9%
11450 1
 
2.9%
14001 1
 
2.9%
Other values (12) 12
35.3%
(Missing) 12
35.3%
ValueCountFrequency (%)
10017 1
2.9%
10922 1
2.9%
10930 1
2.9%
11150 1
2.9%
11450 1
2.9%
11671 1
2.9%
11719 1
2.9%
11916 1
2.9%
12237 1
2.9%
12744 1
2.9%
ValueCountFrequency (%)
18122 1
2.9%
17877 1
2.9%
17583 1
2.9%
15812 1
2.9%
15494 1
2.9%
15056 1
2.9%
14675 1
2.9%
14633 1
2.9%
14582 1
2.9%
14303 1
2.9%

소재지도로명주소
Text

MISSING 

Distinct17
Distinct (%)100.0%
Missing17
Missing (%)50.0%
Memory size404.0 B
2023-12-11T07:06:30.883234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length19
Mean length17.294118
Min length14

Characters and Unicode

Total characters294
Distinct characters68
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

Unique17 ?
Unique (%)100.0%

Sample

1st row경기도 광명시 오리로 643
2nd row경기도 구리시 동구릉로136번길 90
3rd row경기도 군포시 금정로 25
4th row경기도 김포시 통진읍 김포대로 2004
5th row경기도 남양주시 경춘로 997
ValueCountFrequency (%)
경기도 17
 
23.6%
부천시 3
 
4.2%
장내로 1
 
1.4%
9-5 1
 
1.4%
안산시 1
 
1.4%
상록구 1
 
1.4%
양지편로 1
 
1.4%
32 1
 
1.4%
안성시 1
 
1.4%
도기6길 1
 
1.4%
Other values (44) 44
61.1%
2023-12-11T07:06:31.199964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
55
18.7%
경 19
 
6.5%
시 18
 
6.1%
도 18
 
6.1%
기 18
 
6.1%
로 15
 
5.1%
3 12
 
4.1%
1 8
 
2.7%
4 7
 
2.4%
길 6
 
2.0%
Other values (58) 118
40.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 182
61.9%
Space Separator 55
 
18.7%
Decimal Number 55
 
18.7%
Dash Punctuation 2
 
0.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
경 19
 
10.4%
시 18
 
9.9%
도 18
 
9.9%
기 18
 
9.9%
로 15
 
8.2%
길 6
 
3.3%
구 5
 
2.7%
부 5
 
2.7%
안 5
 
2.7%
양 4
 
2.2%
Other values (46) 69
37.9%
Decimal Number
ValueCountFrequency (%)
3 12
21.8%
1 8
14.5%
4 7
12.7%
7 5
9.1%
6 5
9.1%
0 4
 
7.3%
2 4
 
7.3%
9 4
 
7.3%
8 3
 
5.5%
5 3
 
5.5%
Space Separator
ValueCountFrequency (%)
55
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 182
61.9%
Common 112
38.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
경 19
 
10.4%
시 18
 
9.9%
도 18
 
9.9%
기 18
 
9.9%
로 15
 
8.2%
길 6
 
3.3%
구 5
 
2.7%
부 5
 
2.7%
안 5
 
2.7%
양 4
 
2.2%
Other values (46) 69
37.9%
Common
ValueCountFrequency (%)
55
49.1%
3 12
 
10.7%
1 8
 
7.1%
4 7
 
6.2%
7 5
 
4.5%
6 5
 
4.5%
0 4
 
3.6%
2 4
 
3.6%
9 4
 
3.6%
8 3
 
2.7%
Other values (2) 5
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 182
61.9%
ASCII 112
38.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
55
49.1%
3 12
 
10.7%
1 8
 
7.1%
4 7
 
6.2%
7 5
 
4.5%
6 5
 
4.5%
0 4
 
3.6%
2 4
 
3.6%
9 4
 
3.6%
8 3
 
2.7%
Other values (2) 5
 
4.5%
Hangul
ValueCountFrequency (%)
경 19
 
10.4%
시 18
 
9.9%
도 18
 
9.9%
기 18
 
9.9%
로 15
 
8.2%
길 6
 
3.3%
구 5
 
2.7%
부 5
 
2.7%
안 5
 
2.7%
양 4
 
2.2%
Other values (46) 69
37.9%

소재지지번주소
Text

UNIQUE 

Distinct34
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size404.0 B
2023-12-11T07:06:31.405701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length34
Median length24
Mean length18.558824
Min length10

Characters and Unicode

Total characters631
Distinct characters113
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique34 ?
Unique (%)100.0%

Sample

1st row경기도 고양시 일산서구 덕이동
2nd row경기도 광명시 하안동 석산빌딩
3rd row경기도 광주시 송정동 120-8번지
4th row경기도 구리시 인창동 127번지
5th row경기도 군포시 금정동 730-2번지
ValueCountFrequency (%)
경기도 34
 
24.3%
부천시 3
 
2.1%
파주시 2
 
1.4%
김포시 2
 
1.4%
의정부시 2
 
1.4%
안성시 2
 
1.4%
성남시 2
 
1.4%
안산시 2
 
1.4%
시흥시 2
 
1.4%
이천시 1
 
0.7%
Other values (88) 88
62.9%
2023-12-11T07:06:31.767348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
106
 
16.8%
경 37
 
5.9%
기 37
 
5.9%
도 36
 
5.7%
시 35
 
5.5%
동 30
 
4.8%
1 22
 
3.5%
지 18
 
2.9%
번 18
 
2.9%
2 18
 
2.9%
Other values (103) 274
43.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 417
66.1%
Space Separator 106
 
16.8%
Decimal Number 90
 
14.3%
Dash Punctuation 15
 
2.4%
Other Punctuation 1
 
0.2%
Open Punctuation 1
 
0.2%
Close Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
경 37
 
8.9%
기 37
 
8.9%
도 36
 
8.6%
시 35
 
8.4%
동 30
 
7.2%
지 18
 
4.3%
번 18
 
4.3%
정 10
 
2.4%
안 9
 
2.2%
구 8
 
1.9%
Other values (88) 179
42.9%
Decimal Number
ValueCountFrequency (%)
1 22
24.4%
2 18
20.0%
7 9
10.0%
6 9
10.0%
4 7
 
7.8%
0 6
 
6.7%
5 6
 
6.7%
8 5
 
5.6%
3 5
 
5.6%
9 3
 
3.3%
Space Separator
ValueCountFrequency (%)
106
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 15
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 417
66.1%
Common 214
33.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
경 37
 
8.9%
기 37
 
8.9%
도 36
 
8.6%
시 35
 
8.4%
동 30
 
7.2%
지 18
 
4.3%
번 18
 
4.3%
정 10
 
2.4%
안 9
 
2.2%
구 8
 
1.9%
Other values (88) 179
42.9%
Common
ValueCountFrequency (%)
106
49.5%
1 22
 
10.3%
2 18
 
8.4%
- 15
 
7.0%
7 9
 
4.2%
6 9
 
4.2%
4 7
 
3.3%
0 6
 
2.8%
5 6
 
2.8%
8 5
 
2.3%
Other values (5) 11
 
5.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 417
66.1%
ASCII 214
33.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
106
49.5%
1 22
 
10.3%
2 18
 
8.4%
- 15
 
7.0%
7 9
 
4.2%
6 9
 
4.2%
4 7
 
3.3%
0 6
 
2.8%
5 6
 
2.8%
8 5
 
2.3%
Other values (5) 11
 
5.1%
Hangul
ValueCountFrequency (%)
경 37
 
8.9%
기 37
 
8.9%
도 36
 
8.6%
시 35
 
8.4%
동 30
 
7.2%
지 18
 
4.3%
번 18
 
4.3%
정 10
 
2.4%
안 9
 
2.2%
구 8
 
1.9%
Other values (88) 179
42.9%

인허가일자
Real number (ℝ)

Distinct20
Distinct (%)58.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20031894
Minimum19920414
Maximum20170323
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size438.0 B
2023-12-11T07:06:31.884565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19920414
5-th percentile19997351
Q120003293
median20015966
Q320055177
95-th percentile20125002
Maximum20170323
Range249909
Interquartile range (IQR)51883.5

Descriptive statistics

Standard deviation49010.738
Coefficient of variation (CV)0.0024466352
Kurtosis2.6510399
Mean20031894
Median Absolute Deviation (MAD)15142
Skewness1.1966715
Sum6.8108441 × 108
Variance2.4020524 × 109
MonotonicityNot monotonic
2023-12-11T07:06:31.985779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
20010701 7
20.6%
20000824 6
17.6%
20020701 2
 
5.9%
20021231 2
 
5.9%
20021201 2
 
5.9%
20000820 1
 
2.9%
20080125 1
 
2.9%
20060801 1
 
2.9%
20170323 1
 
2.9%
20080820 1
 
2.9%
Other values (10) 10
29.4%
ValueCountFrequency (%)
19920414 1
 
2.9%
19990909 1
 
2.9%
20000820 1
 
2.9%
20000824 6
17.6%
20010701 7
20.6%
20011231 1
 
2.9%
20020701 2
 
5.9%
20021201 2
 
5.9%
20021231 2
 
5.9%
20030801 1
 
2.9%
ValueCountFrequency (%)
20170323 1
2.9%
20170105 1
2.9%
20100716 1
2.9%
20080820 1
2.9%
20080612 1
2.9%
20080125 1
2.9%
20080115 1
2.9%
20060801 1
2.9%
20060102 1
2.9%
20040401 1
2.9%

영업상태명
Categorical

CONSTANT 

Distinct1
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size404.0 B
운영중
34 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
운영중 34
100.0%

Length

2023-12-11T07:06:32.097846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T07:06:32.181376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
운영중 34
100.0%

입소정원(명)
Real number (ℝ)

MISSING  ZEROS 

Distinct11
Distinct (%)33.3%
Missing1
Missing (%)2.9%
Infinite0
Infinite (%)0.0%
Mean34.575758
Minimum0
Maximum240
Zeros22
Zeros (%)64.7%
Negative0
Negative (%)0.0%
Memory size438.0 B
2023-12-11T07:06:32.255924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q361
95-th percentile150
Maximum240
Range240
Interquartile range (IQR)61

Descriptive statistics

Standard deviation60.601171
Coefficient of variation (CV)1.752707
Kurtosis3.0882545
Mean34.575758
Median Absolute Deviation (MAD)0
Skewness1.8419258
Sum1141
Variance3672.5019
MonotonicityNot monotonic
2023-12-11T07:06:32.346192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
0 22
64.7%
150 2
 
5.9%
90 1
 
2.9%
130 1
 
2.9%
60 1
 
2.9%
100 1
 
2.9%
5 1
 
2.9%
240 1
 
2.9%
75 1
 
2.9%
61 1
 
2.9%
ValueCountFrequency (%)
0 22
64.7%
5 1
 
2.9%
60 1
 
2.9%
61 1
 
2.9%
75 1
 
2.9%
80 1
 
2.9%
90 1
 
2.9%
100 1
 
2.9%
130 1
 
2.9%
150 2
 
5.9%
ValueCountFrequency (%)
240 1
2.9%
150 2
5.9%
130 1
2.9%
100 1
2.9%
90 1
2.9%
80 1
2.9%
75 1
2.9%
61 1
2.9%
60 1
2.9%
5 1
2.9%

자격소유인원수(명)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct10
Distinct (%)29.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.3529412
Minimum0
Maximum12
Zeros7
Zeros (%)20.6%
Negative0
Negative (%)0.0%
Memory size438.0 B
2023-12-11T07:06:32.436113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12
median4
Q36.75
95-th percentile10
Maximum12
Range12
Interquartile range (IQR)4.75

Descriptive statistics

Standard deviation3.283405
Coefficient of variation (CV)0.75429575
Kurtosis-0.34111762
Mean4.3529412
Median Absolute Deviation (MAD)2.5
Skewness0.40368423
Sum148
Variance10.780749
MonotonicityNot monotonic
2023-12-11T07:06:32.539843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
0 7
20.6%
4 7
20.6%
7 5
14.7%
5 4
11.8%
10 3
8.8%
6 2
 
5.9%
3 2
 
5.9%
2 2
 
5.9%
1 1
 
2.9%
12 1
 
2.9%
ValueCountFrequency (%)
0 7
20.6%
1 1
 
2.9%
2 2
 
5.9%
3 2
 
5.9%
4 7
20.6%
5 4
11.8%
6 2
 
5.9%
7 5
14.7%
10 3
8.8%
12 1
 
2.9%
ValueCountFrequency (%)
12 1
 
2.9%
10 3
8.8%
7 5
14.7%
6 2
 
5.9%
5 4
11.8%
4 7
20.6%
3 2
 
5.9%
2 2
 
5.9%
1 1
 
2.9%
0 7
20.6%

총인원수(명)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct9
Distinct (%)26.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.6470588
Minimum0
Maximum12
Zeros4
Zeros (%)11.8%
Negative0
Negative (%)0.0%
Memory size438.0 B
2023-12-11T07:06:32.640645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q14.25
median6
Q36
95-th percentile10
Maximum12
Range12
Interquartile range (IQR)1.75

Descriptive statistics

Standard deviation2.9734416
Coefficient of variation (CV)0.52654694
Kurtosis0.14368529
Mean5.6470588
Median Absolute Deviation (MAD)1.5
Skewness-0.19298874
Sum192
Variance8.8413547
MonotonicityNot monotonic
2023-12-11T07:06:32.743697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
6 12
35.3%
5 5
14.7%
4 4
 
11.8%
0 4
 
11.8%
9 3
 
8.8%
10 3
 
8.8%
2 1
 
2.9%
12 1
 
2.9%
8 1
 
2.9%
ValueCountFrequency (%)
0 4
 
11.8%
2 1
 
2.9%
4 4
 
11.8%
5 5
14.7%
6 12
35.3%
8 1
 
2.9%
9 3
 
8.8%
10 3
 
8.8%
12 1
 
2.9%
ValueCountFrequency (%)
12 1
 
2.9%
10 3
 
8.8%
9 3
 
8.8%
8 1
 
2.9%
6 12
35.3%
5 5
14.7%
4 4
 
11.8%
2 1
 
2.9%
0 4
 
11.8%

WGS84위도
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct20
Distinct (%)100.0%
Missing14
Missing (%)41.2%
Infinite0
Infinite (%)0.0%
Mean37.506455
Minimum37.003286
Maximum37.844973
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size438.0 B
2023-12-11T07:06:32.846157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.003286
5-th percentile37.151616
Q137.389528
median37.486515
Q337.692988
95-th percentile37.768526
Maximum37.844973
Range0.84168654
Interquartile range (IQR)0.3034604

Descriptive statistics

Standard deviation0.21656249
Coefficient of variation (CV)0.0057740058
Kurtosis0.056957905
Mean37.506455
Median Absolute Deviation (MAD)0.14469192
Skewness-0.47546364
Sum750.12909
Variance0.04689931
MonotonicityNot monotonic
2023-12-11T07:06:32.948184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
37.3090074993 1
 
2.9%
37.7645026838 1
 
2.9%
37.754599675 1
 
2.9%
37.7258069814 1
 
2.9%
37.7414619276 1
 
2.9%
37.1594228815 1
 
2.9%
37.8449726182 1
 
2.9%
37.3971536173 1
 
2.9%
37.0032860743 1
 
2.9%
37.4586249849 1
 
2.9%
Other values (10) 10
29.4%
(Missing) 14
41.2%
ValueCountFrequency (%)
37.0032860743 1
2.9%
37.1594228815 1
2.9%
37.3090074993 1
2.9%
37.3456735054 1
2.9%
37.3666498836 1
2.9%
37.3971536173 1
2.9%
37.4168016927 1
2.9%
37.4399769656 1
2.9%
37.4586249849 1
2.9%
37.4832458588 1
2.9%
ValueCountFrequency (%)
37.8449726182 1
2.9%
37.7645026838 1
2.9%
37.754599675 1
2.9%
37.7414619276 1
2.9%
37.7258069814 1
2.9%
37.6820484483 1
2.9%
37.6350573551 1
2.9%
37.6159259498 1
2.9%
37.4950868721 1
2.9%
37.4897849896 1
2.9%

WGS84경도
Real number (ℝ)

MISSING 

Distinct20
Distinct (%)100.0%
Missing14
Missing (%)41.2%
Infinite0
Infinite (%)0.0%
Mean126.95738
Minimum126.62102
Maximum127.26362
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size438.0 B
2023-12-11T07:06:33.060137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.62102
5-th percentile126.73538
Q1126.78307
median126.93146
Q3127.08443
95-th percentile127.25674
Maximum127.26362
Range0.64260456
Interquartile range (IQR)0.30136281

Descriptive statistics

Standard deviation0.19125569
Coefficient of variation (CV)0.0015064558
Kurtosis-1.1444778
Mean126.95738
Median Absolute Deviation (MAD)0.14897569
Skewness0.13711125
Sum2539.1477
Variance0.03657874
MonotonicityNot monotonic
2023-12-11T07:06:33.171120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
126.8508113384 1
 
2.9%
126.7765271419 1
 
2.9%
126.7813346334 1
 
2.9%
127.0564630943 1
 
2.9%
127.0420459374 1
 
2.9%
127.0563812707 1
 
2.9%
127.0644111467 1
 
2.9%
126.9203469422 1
 
2.9%
127.2636231114 1
 
2.9%
126.8774712115 1
 
2.9%
Other values (10) 10
29.4%
(Missing) 14
41.2%
ValueCountFrequency (%)
126.6210185522 1
2.9%
126.7413999009 1
2.9%
126.7765271419 1
2.9%
126.7765662423 1
2.9%
126.7813346334 1
2.9%
126.7836419533 1
2.9%
126.8086332578 1
2.9%
126.8508113384 1
2.9%
126.8774712115 1
2.9%
126.9203469422 1
2.9%
ValueCountFrequency (%)
127.2636231114 1
2.9%
127.2563741097 1
2.9%
127.2124244679 1
2.9%
127.1711428952 1
2.9%
127.144478278 1
2.9%
127.0644111467 1
2.9%
127.0564630943 1
2.9%
127.0563812707 1
2.9%
127.0420459374 1
2.9%
126.942581016 1
2.9%

Interactions

2023-12-11T07:06:28.604168image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:06:25.076167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:06:25.691473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:06:26.213213image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:06:26.718078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:06:27.250217image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:06:27.829738image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:06:28.686655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:06:25.155645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:06:25.766565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:06:26.288695image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:06:26.801402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:06:27.326463image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:06:27.929410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:06:28.776546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:06:25.229835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:06:25.831841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:06:26.363093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:06:26.877228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:06:27.396123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:06:28.241969image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:06:28.863329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:06:25.305857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:06:25.897770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:06:26.429799image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:06:26.962224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:06:27.467746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:06:28.308183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:06:28.941615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:06:25.384182image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:06:25.977877image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:06:26.503057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:06:27.035280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:06:27.546472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:06:28.375731image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:06:29.022982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:06:25.470804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:06:26.058912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:06:26.574886image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:06:27.110968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:06:27.646741image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:06:28.441207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:06:29.091216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:06:25.575954image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:06:26.132204image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:06:26.638429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:06:27.180818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:06:27.752898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:06:28.519399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T07:06:33.257535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군명사업장명소재지우편번호소재지도로명주소소재지지번주소인허가일자입소정원(명)자격소유인원수(명)총인원수(명)WGS84위도WGS84경도
시군명1.0001.0001.0001.0001.0000.8500.8240.6930.8470.9951.000
사업장명1.0001.0001.0001.0001.0001.0000.8100.9430.9661.0001.000
소재지우편번호1.0001.0001.0001.0001.0000.4070.7440.5920.3590.8960.905
소재지도로명주소1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
소재지지번주소1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
인허가일자0.8501.0000.4071.0001.0001.0000.8990.0000.6310.0000.537
입소정원(명)0.8240.8100.7441.0001.0000.8991.0000.6190.6790.0000.795
자격소유인원수(명)0.6930.9430.5921.0001.0000.0000.6191.0000.6800.6200.264
총인원수(명)0.8470.9660.3591.0001.0000.6310.6790.6801.0000.0000.522
WGS84위도0.9951.0000.8961.0001.0000.0000.0000.6200.0001.0000.000
WGS84경도1.0001.0000.9051.0001.0000.5370.7950.2640.5220.0001.000
2023-12-11T07:06:33.414076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
소재지우편번호인허가일자입소정원(명)자격소유인원수(명)총인원수(명)WGS84위도WGS84경도
소재지우편번호1.000-0.1410.108-0.331-0.493-0.8900.122
인허가일자-0.1411.0000.2170.1330.2250.065-0.046
입소정원(명)0.1080.2171.0000.4410.262-0.3560.125
자격소유인원수(명)-0.3310.1330.4411.0000.6270.100-0.185
총인원수(명)-0.4930.2250.2620.6271.0000.436-0.200
WGS84위도-0.8900.065-0.3560.1000.4361.000-0.192
WGS84경도0.122-0.0460.125-0.185-0.200-0.1921.000

Missing values

2023-12-11T07:06:29.190051image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T07:06:29.338307image/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.
2023-12-11T07:06:29.445192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

시군명사업장명소재지우편번호소재지도로명주소소재지지번주소인허가일자영업상태명입소정원(명)자격소유인원수(명)총인원수(명)WGS84위도WGS84경도
0고양시고양지역자활센터<NA><NA>경기도 고양시 일산서구 덕이동20010701운영중005<NA><NA>
1광명시경기광명지역자활센터14303경기도 광명시 오리로 643경기도 광명시 하안동 석산빌딩20060102운영중9010937.458625126.877471
2광주시경기광주 지역자활센터12744<NA>경기도 광주시 송정동 120-8번지20030801운영중06637.416802127.256374
3구리시구리지역자활센터11916경기도 구리시 동구릉로136번길 90경기도 구리시 인창동 127번지20000824운영중00637.615926127.144478
4군포시군포지역자활센터15812경기도 군포시 금정로 25경기도 군포시 금정동 730-2번지20020701운영중1303637.36665126.942581
5김포시경기김포지역자활센터<NA><NA>경기도 김포시 북변동20021231운영중6014<NA><NA>
6김포시경기김포지역자활센터10017경기도 김포시 통진읍 김포대로 2004경기도 김포시 통진읍 도사리 624-12번지20021231운영중05637.682048126.621019
7남양주시경기남양주지역자활센터12237경기도 남양주시 경춘로 997경기도 남양주시 금곡동 158-14번지20010701운영중00637.635057127.212424
8부천시경기부천원미지역자활센터14582경기도 부천시 부흥로303번길 8경기도 부천시 중동 1122번지20000824운영중04637.495087126.776566
9부천시경기부천나눔지역자활센터14633경기도 부천시 장말로 376경기도 부천시 심곡동 성보빌딩20000824운영중04637.489785126.783642
시군명사업장명소재지우편번호소재지도로명주소소재지지번주소인허가일자영업상태명입소정원(명)자격소유인원수(명)총인원수(명)WGS84위도WGS84경도
24용인시용인지역자활센터<NA><NA>경기도 용인시 처인구 삼가동20010701운영중045<NA><NA>
25의정부시의정부지역자활센터11671경기도 의정부시 흥선로 138경기도 의정부시 의정부동 427-23번지20000820운영중05637.741462127.042046
26의정부시의정부시종합사회복지관11719<NA>경기도 의정부시 장암동 5번지19920414운영중00037.725807127.056463
27이천시이천지역자활센터<NA><NA>경기도 이천시 신둔면 수하리20170105운영중<NA>44<NA><NA>
28파주시파주지역자활센터10922경기도 파주시 가나무로 143경기도 파주시 금능동 211-5번지 202,203호20021201운영중15071037.7546126.781335
29파주시파주지역자활10930<NA>경기도 파주시 금촌동 51-49번지20021201운영중071037.764503126.776527
30평택시평택지역자활센터17877<NA>경기도 평택시 합정동20080820운영중000<NA><NA>
31포천시포천지역자활센터11150<NA>경기도 포천시 어룡동 개성인삼하나로마트20170323운영중6156<NA><NA>
32하남시하남지역자활센터<NA><NA>경기도 하남시 하산곡동20060801운영중8044<NA><NA>
33화성시화성지역자활센터<NA><NA>경기도 화성시 향남읍 화성종합경기타운 주경기장 16게이트 1층20080125운영중049<NA><NA>