Overview

Dataset statistics

Number of variables12
Number of observations126
Missing cells263
Missing cells (%)17.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory12.8 KiB
Average record size in memory104.0 B

Variable types

Categorical2
Text3
Numeric7

Dataset

Description장애인주간보호시설 현황
Author행정안전부
URLhttps://data.gg.go.kr/portal/data/service/selectServicePage.do?&infId=PFK4TUL85GSQ0E4EYW4E13907332&infSeq=1

Alerts

총인원수(명) is highly overall correlated with 영업상태명High correlation
소재지우편번호 is highly overall correlated with WGS84위도 and 1 other fieldsHigh correlation
WGS84위도 is highly overall correlated with 소재지우편번호 and 1 other fieldsHigh correlation
WGS84경도 is highly overall correlated with 시군명High correlation
시군명 is highly overall correlated with 소재지우편번호 and 2 other fieldsHigh correlation
영업상태명 is highly overall correlated with 총인원수(명)High correlation
영업상태명 is highly imbalanced (88.2%)Imbalance
자격소유인원수(명) has 25 (19.8%) missing valuesMissing
총인원수(명) has 29 (23.0%) missing valuesMissing
소재지도로명주소 has 56 (44.4%) missing valuesMissing
소재지우편번호 has 49 (38.9%) missing valuesMissing
WGS84위도 has 52 (41.3%) missing valuesMissing
WGS84경도 has 52 (41.3%) missing valuesMissing
입소정원(명) has 2 (1.6%) zerosZeros
자격소유인원수(명) has 9 (7.1%) zerosZeros
총인원수(명) has 2 (1.6%) zerosZeros

Reproduction

Analysis started2023-12-10 22:32:07.987897
Analysis finished2023-12-10 22:32:13.757942
Duration5.77 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군명
Categorical

HIGH CORRELATION 

Distinct29
Distinct (%)23.0%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
부천시
12 
성남시
12 
안산시
12 
고양시
9 
용인시
9 
Other values (24)
72 

Length

Max length4
Median length3
Mean length3.0714286
Min length3

Unique

Unique4 ?
Unique (%)3.2%

Sample

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

Common Values

ValueCountFrequency (%)
부천시 12
 
9.5%
성남시 12
 
9.5%
안산시 12
 
9.5%
고양시 9
 
7.1%
용인시 9
 
7.1%
평택시 6
 
4.8%
시흥시 6
 
4.8%
화성시 6
 
4.8%
안양시 5
 
4.0%
김포시 5
 
4.0%
Other values (19) 44
34.9%

Length

2023-12-11T07:32:13.819631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
부천시 12
 
9.5%
안산시 12
 
9.5%
성남시 12
 
9.5%
고양시 9
 
7.1%
용인시 9
 
7.1%
평택시 6
 
4.8%
시흥시 6
 
4.8%
화성시 6
 
4.8%
안양시 5
 
4.0%
김포시 5
 
4.0%
Other values (19) 44
34.9%

사업장명
Text

Distinct120
Distinct (%)95.2%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2023-12-11T07:32:14.000541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length31
Median length20
Mean length11.873016
Min length3

Characters and Unicode

Total characters1496
Distinct characters163
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique115 ?
Unique (%)91.3%

Sample

1st row고양시장애인주간보호센터
2nd row고양시장애인종합복지관부설주간보호센터
3rd row원당주간보호센터
4th row원당사회복지관 무지개장애인주간보호센터
5th row홀트장애인주간보호센터
ValueCountFrequency (%)
주간보호센터 9
 
5.2%
부설 7
 
4.0%
장애인주간보호센터 6
 
3.4%
장애인주간보호시설 3
 
1.7%
김포시 3
 
1.7%
행복한길 3
 
1.7%
장애인 2
 
1.1%
마음톡톡센터 2
 
1.1%
주간보호시설 2
 
1.1%
물댄동산장애인주간보호시설 2
 
1.1%
Other values (131) 135
77.6%
2023-12-11T07:32:14.325216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 111
 
7.4%
간 100
 
6.7%
호 99
 
6.6%
보 98
 
6.6%
인 93
 
6.2%
장 84
 
5.6%
애 84
 
5.6%
터 81
 
5.4%
시 74
 
4.9%
센 74
 
4.9%
Other values (153) 598
40.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1432
95.7%
Space Separator 48
 
3.2%
Open Punctuation 5
 
0.3%
Close Punctuation 5
 
0.3%
Lowercase Letter 3
 
0.2%
Math Symbol 2
 
0.1%
Uppercase Letter 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 111
 
7.8%
간 100
 
7.0%
호 99
 
6.9%
보 98
 
6.8%
인 93
 
6.5%
장 84
 
5.9%
애 84
 
5.9%
터 81
 
5.7%
시 74
 
5.2%
센 74
 
5.2%
Other values (145) 534
37.3%
Lowercase Letter
ValueCountFrequency (%)
l 1
33.3%
b 1
33.3%
e 1
33.3%
Space Separator
ValueCountFrequency (%)
48
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%
Uppercase Letter
ValueCountFrequency (%)
A 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1432
95.7%
Common 60
 
4.0%
Latin 4
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 111
 
7.8%
간 100
 
7.0%
호 99
 
6.9%
보 98
 
6.8%
인 93
 
6.5%
장 84
 
5.9%
애 84
 
5.9%
터 81
 
5.7%
시 74
 
5.2%
센 74
 
5.2%
Other values (145) 534
37.3%
Common
ValueCountFrequency (%)
48
80.0%
( 5
 
8.3%
) 5
 
8.3%
~ 2
 
3.3%
Latin
ValueCountFrequency (%)
l 1
25.0%
b 1
25.0%
A 1
25.0%
e 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1432
95.7%
ASCII 64
 
4.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 111
 
7.8%
간 100
 
7.0%
호 99
 
6.9%
보 98
 
6.8%
인 93
 
6.5%
장 84
 
5.9%
애 84
 
5.9%
터 81
 
5.7%
시 74
 
5.2%
센 74
 
5.2%
Other values (145) 534
37.3%
ASCII
ValueCountFrequency (%)
48
75.0%
( 5
 
7.8%
) 5
 
7.8%
~ 2
 
3.1%
l 1
 
1.6%
b 1
 
1.6%
A 1
 
1.6%
e 1
 
1.6%

인허가일자
Real number (ℝ)

Distinct120
Distinct (%)95.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20087757
Minimum19980218
Maximum20180814
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2023-12-11T07:32:14.455834image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19980218
5-th percentile19990297
Q120050328
median20090760
Q320130678
95-th percentile20161080
Maximum20180814
Range200596
Interquartile range (IQR)80350

Descriptive statistics

Standard deviation54535.171
Coefficient of variation (CV)0.0027148463
Kurtosis-0.8505036
Mean20087757
Median Absolute Deviation (MAD)40059.5
Skewness-0.33918178
Sum2.5310573 × 109
Variance2.9740849 × 109
MonotonicityNot monotonic
2023-12-11T07:32:14.609182image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20120102 2
 
1.6%
20040302 2
 
1.6%
20030219 2
 
1.6%
20050201 2
 
1.6%
20170102 2
 
1.6%
20060613 2
 
1.6%
19980801 1
 
0.8%
20061204 1
 
0.8%
20100503 1
 
0.8%
20130506 1
 
0.8%
Other values (110) 110
87.3%
ValueCountFrequency (%)
19980218 1
0.8%
19980801 1
0.8%
19980909 1
0.8%
19981109 1
0.8%
19990101 1
0.8%
19990126 1
0.8%
19990226 1
0.8%
19990510 1
0.8%
19990916 1
0.8%
19991004 1
0.8%
ValueCountFrequency (%)
20180814 1
0.8%
20180620 1
0.8%
20170308 1
0.8%
20170118 1
0.8%
20170102 2
1.6%
20161101 1
0.8%
20161017 1
0.8%
20160826 1
0.8%
20160601 1
0.8%
20160513 1
0.8%

영업상태명
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
운영중
124 
휴업 등
 
2

Length

Max length4
Median length3
Mean length3.015873
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
운영중 124
98.4%
휴업 등 2
 
1.6%

Length

2023-12-11T07:32:14.768047image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T07:32:14.855475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
운영중 124
96.9%
휴업 2
 
1.6%
등 2
 
1.6%

입소정원(명)
Real number (ℝ)

ZEROS 

Distinct21
Distinct (%)16.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20.444444
Minimum0
Maximum120
Zeros2
Zeros (%)1.6%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2023-12-11T07:32:14.936408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile10
Q113.5
median17
Q325
95-th percentile40
Maximum120
Range120
Interquartile range (IQR)11.5

Descriptive statistics

Standard deviation12.673472
Coefficient of variation (CV)0.61989808
Kurtosis29.933321
Mean20.444444
Median Absolute Deviation (MAD)5
Skewness4.2061916
Sum2576
Variance160.61689
MonotonicityNot monotonic
2023-12-11T07:32:15.034752image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
20 22
17.5%
30 20
15.9%
15 17
13.5%
10 15
11.9%
12 11
8.7%
16 11
8.7%
40 4
 
3.2%
17 4
 
3.2%
25 3
 
2.4%
13 3
 
2.4%
Other values (11) 16
12.7%
ValueCountFrequency (%)
0 2
 
1.6%
10 15
11.9%
11 1
 
0.8%
12 11
8.7%
13 3
 
2.4%
15 17
13.5%
16 11
8.7%
17 4
 
3.2%
18 2
 
1.6%
20 22
17.5%
ValueCountFrequency (%)
120 1
 
0.8%
50 2
 
1.6%
44 1
 
0.8%
40 4
 
3.2%
30 20
15.9%
28 2
 
1.6%
25 3
 
2.4%
24 2
 
1.6%
23 1
 
0.8%
22 1
 
0.8%

자격소유인원수(명)
Real number (ℝ)

MISSING  ZEROS 

Distinct8
Distinct (%)7.9%
Missing25
Missing (%)19.8%
Infinite0
Infinite (%)0.0%
Mean3.049505
Minimum0
Maximum8
Zeros9
Zeros (%)7.1%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2023-12-11T07:32:15.128953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12
median3
Q34
95-th percentile5
Maximum8
Range8
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.5580516
Coefficient of variation (CV)0.51091951
Kurtosis1.7209807
Mean3.049505
Median Absolute Deviation (MAD)1
Skewness0.38554979
Sum308
Variance2.4275248
MonotonicityNot monotonic
2023-12-11T07:32:15.249033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
3 41
32.5%
4 20
15.9%
2 16
 
12.7%
0 9
 
7.1%
5 8
 
6.3%
1 3
 
2.4%
7 2
 
1.6%
8 2
 
1.6%
(Missing) 25
19.8%
ValueCountFrequency (%)
0 9
 
7.1%
1 3
 
2.4%
2 16
 
12.7%
3 41
32.5%
4 20
15.9%
5 8
 
6.3%
7 2
 
1.6%
8 2
 
1.6%
ValueCountFrequency (%)
8 2
 
1.6%
7 2
 
1.6%
5 8
 
6.3%
4 20
15.9%
3 41
32.5%
2 16
 
12.7%
1 3
 
2.4%
0 9
 
7.1%

총인원수(명)
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct14
Distinct (%)14.4%
Missing29
Missing (%)23.0%
Infinite0
Infinite (%)0.0%
Mean4.5154639
Minimum0
Maximum30
Zeros2
Zeros (%)1.6%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2023-12-11T07:32:15.368145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2
Q13
median4
Q34
95-th percentile9.2
Maximum30
Range30
Interquartile range (IQR)1

Descriptive statistics

Standard deviation4.2820201
Coefficient of variation (CV)0.94830125
Kurtosis22.881879
Mean4.5154639
Median Absolute Deviation (MAD)1
Skewness4.5138291
Sum438
Variance18.335696
MonotonicityNot monotonic
2023-12-11T07:32:15.468073image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
3 36
28.6%
4 31
24.6%
2 7
 
5.6%
5 7
 
5.6%
8 3
 
2.4%
6 3
 
2.4%
10 2
 
1.6%
0 2
 
1.6%
28 1
 
0.8%
20 1
 
0.8%
Other values (4) 4
 
3.2%
(Missing) 29
23.0%
ValueCountFrequency (%)
0 2
 
1.6%
1 1
 
0.8%
2 7
 
5.6%
3 36
28.6%
4 31
24.6%
5 7
 
5.6%
6 3
 
2.4%
7 1
 
0.8%
8 3
 
2.4%
9 1
 
0.8%
ValueCountFrequency (%)
30 1
 
0.8%
28 1
 
0.8%
20 1
 
0.8%
10 2
 
1.6%
9 1
 
0.8%
8 3
 
2.4%
7 1
 
0.8%
6 3
 
2.4%
5 7
 
5.6%
4 31
24.6%

소재지도로명주소
Text

MISSING 

Distinct64
Distinct (%)91.4%
Missing56
Missing (%)44.4%
Memory size1.1 KiB
2023-12-11T07:32:15.707975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length25
Mean length18.8
Min length14

Characters and Unicode

Total characters1316
Distinct characters135
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

Unique59 ?
Unique (%)84.3%

Sample

1st row경기도 고양시 일산서구 고양대로672번길 15-7
2nd row경기도 고양시 일산서구 탄현로 139
3rd row경기도 고양시 덕양구 호국로 809
4th row경기도 고양시 덕양구 호국로716번길 13-11
5th row경기도 고양시 일산서구 탄현로 42
ValueCountFrequency (%)
경기도 70
 
22.1%
부천시 11
 
3.5%
안산시 8
 
2.5%
고양시 7
 
2.2%
상록구 6
 
1.9%
용인시 5
 
1.6%
일산서구 4
 
1.3%
안양시 4
 
1.3%
중보로 4
 
1.3%
49 3
 
0.9%
Other values (159) 195
61.5%
2023-12-11T07:32:16.130986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
247
18.8%
경 74
 
5.6%
시 73
 
5.5%
기 73
 
5.5%
도 71
 
5.4%
로 61
 
4.6%
1 44
 
3.3%
2 39
 
3.0%
길 32
 
2.4%
구 30
 
2.3%
Other values (125) 572
43.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 819
62.2%
Space Separator 247
 
18.8%
Decimal Number 238
 
18.1%
Dash Punctuation 12
 
0.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
경 74
 
9.0%
시 73
 
8.9%
기 73
 
8.9%
도 71
 
8.7%
로 61
 
7.4%
길 32
 
3.9%
구 30
 
3.7%
안 23
 
2.8%
번 20
 
2.4%
양 20
 
2.4%
Other values (113) 342
41.8%
Decimal Number
ValueCountFrequency (%)
1 44
18.5%
2 39
16.4%
9 25
10.5%
4 23
9.7%
3 22
9.2%
5 22
9.2%
7 17
 
7.1%
6 17
 
7.1%
8 17
 
7.1%
0 12
 
5.0%
Space Separator
ValueCountFrequency (%)
247
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 12
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 819
62.2%
Common 497
37.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
경 74
 
9.0%
시 73
 
8.9%
기 73
 
8.9%
도 71
 
8.7%
로 61
 
7.4%
길 32
 
3.9%
구 30
 
3.7%
안 23
 
2.8%
번 20
 
2.4%
양 20
 
2.4%
Other values (113) 342
41.8%
Common
ValueCountFrequency (%)
247
49.7%
1 44
 
8.9%
2 39
 
7.8%
9 25
 
5.0%
4 23
 
4.6%
3 22
 
4.4%
5 22
 
4.4%
7 17
 
3.4%
6 17
 
3.4%
8 17
 
3.4%
Other values (2) 24
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 819
62.2%
ASCII 497
37.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
247
49.7%
1 44
 
8.9%
2 39
 
7.8%
9 25
 
5.0%
4 23
 
4.6%
3 22
 
4.4%
5 22
 
4.4%
7 17
 
3.4%
6 17
 
3.4%
8 17
 
3.4%
Other values (2) 24
 
4.8%
Hangul
ValueCountFrequency (%)
경 74
 
9.0%
시 73
 
8.9%
기 73
 
8.9%
도 71
 
8.7%
로 61
 
7.4%
길 32
 
3.9%
구 30
 
3.7%
안 23
 
2.8%
번 20
 
2.4%
양 20
 
2.4%
Other values (113) 342
41.8%

소재지지번주소
Text

Distinct123
Distinct (%)97.6%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2023-12-11T07:32:16.419110image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length38
Median length28
Mean length19.531746
Min length10

Characters and Unicode

Total characters2461
Distinct characters178
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

Unique120 ?
Unique (%)95.2%

Sample

1st row경기도 고양시 일산서구 일산동 627-4번지
2nd row경기도 고양시 일산서구 탄현동 111-1번지
3rd row경기도 고양시 덕양구 주교동 620-2번지
4th row경기도 고양시 덕양구 성사동 736-2번지
5th row경기도 고양시 일산서구 탄현동 41-1번지
ValueCountFrequency (%)
경기도 126
 
22.2%
부천시 12
 
2.1%
안산시 12
 
2.1%
성남시 12
 
2.1%
용인시 9
 
1.6%
고양시 9
 
1.6%
상록구 8
 
1.4%
분당구 7
 
1.2%
시흥시 6
 
1.1%
평택시 6
 
1.1%
Other values (259) 360
63.5%
2023-12-11T07:32:16.823103image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
441
 
17.9%
도 131
 
5.3%
기 130
 
5.3%
시 129
 
5.2%
경 126
 
5.1%
동 110
 
4.5%
지 77
 
3.1%
1 68
 
2.8%
번 63
 
2.6%
- 52
 
2.1%
Other values (168) 1134
46.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1651
67.1%
Space Separator 441
 
17.9%
Decimal Number 314
 
12.8%
Dash Punctuation 52
 
2.1%
Close Punctuation 1
 
< 0.1%
Open Punctuation 1
 
< 0.1%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
도 131
 
7.9%
기 130
 
7.9%
시 129
 
7.8%
경 126
 
7.6%
동 110
 
6.7%
지 77
 
4.7%
번 63
 
3.8%
구 51
 
3.1%
양 32
 
1.9%
안 30
 
1.8%
Other values (153) 772
46.8%
Decimal Number
ValueCountFrequency (%)
1 68
21.7%
4 38
12.1%
0 33
10.5%
7 32
10.2%
2 31
9.9%
6 30
9.6%
3 26
 
8.3%
5 20
 
6.4%
8 19
 
6.1%
9 17
 
5.4%
Space Separator
ValueCountFrequency (%)
441
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 52
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1651
67.1%
Common 810
32.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
도 131
 
7.9%
기 130
 
7.9%
시 129
 
7.8%
경 126
 
7.6%
동 110
 
6.7%
지 77
 
4.7%
번 63
 
3.8%
구 51
 
3.1%
양 32
 
1.9%
안 30
 
1.8%
Other values (153) 772
46.8%
Common
ValueCountFrequency (%)
441
54.4%
1 68
 
8.4%
- 52
 
6.4%
4 38
 
4.7%
0 33
 
4.1%
7 32
 
4.0%
2 31
 
3.8%
6 30
 
3.7%
3 26
 
3.2%
5 20
 
2.5%
Other values (5) 39
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1651
67.1%
ASCII 810
32.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
441
54.4%
1 68
 
8.4%
- 52
 
6.4%
4 38
 
4.7%
0 33
 
4.1%
7 32
 
4.0%
2 31
 
3.8%
6 30
 
3.7%
3 26
 
3.2%
5 20
 
2.5%
Other values (5) 39
 
4.8%
Hangul
ValueCountFrequency (%)
도 131
 
7.9%
기 130
 
7.9%
시 129
 
7.8%
경 126
 
7.6%
동 110
 
6.7%
지 77
 
4.7%
번 63
 
3.8%
구 51
 
3.1%
양 32
 
1.9%
안 30
 
1.8%
Other values (153) 772
46.8%

소재지우편번호
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct67
Distinct (%)87.0%
Missing49
Missing (%)38.9%
Infinite0
Infinite (%)0.0%
Mean14001.558
Minimum10011
Maximum18598
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2023-12-11T07:32:16.963927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10011
5-th percentile10249
Q112236
median14294
Q315495
95-th percentile17930.8
Maximum18598
Range8587
Interquartile range (IQR)3259

Descriptive statistics

Standard deviation2298.103
Coefficient of variation (CV)0.16413194
Kurtosis-0.78516915
Mean14001.558
Median Absolute Deviation (MAD)1581
Skewness-0.015682673
Sum1078120
Variance5281277.2
MonotonicityNot monotonic
2023-12-11T07:32:17.086782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
15495 4
 
3.2%
13805 2
 
1.6%
14692 2
 
1.6%
14548 2
 
1.6%
14544 2
 
1.6%
12236 2
 
1.6%
10249 2
 
1.6%
15275 2
 
1.6%
13968 1
 
0.8%
17596 1
 
0.8%
Other values (57) 57
45.2%
(Missing) 49
38.9%
ValueCountFrequency (%)
10011 1
0.8%
10111 1
0.8%
10239 1
0.8%
10249 2
1.6%
10324 1
0.8%
10353 1
0.8%
10445 1
0.8%
10462 1
0.8%
10469 1
0.8%
11151 1
0.8%
ValueCountFrequency (%)
18598 1
0.8%
18298 1
0.8%
18143 1
0.8%
17994 1
0.8%
17915 1
0.8%
17596 1
0.8%
17321 1
0.8%
17039 1
0.8%
17038 1
0.8%
16929 1
0.8%

WGS84위도
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct68
Distinct (%)91.9%
Missing52
Missing (%)41.3%
Infinite0
Infinite (%)0.0%
Mean37.454905
Minimum36.957772
Maximum37.907415
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2023-12-11T07:32:17.213677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum36.957772
5-th percentile37.184474
Q137.336514
median37.434076
Q337.590964
95-th percentile37.739767
Maximum37.907415
Range0.94964292
Interquartile range (IQR)0.2544491

Descriptive statistics

Standard deviation0.18932859
Coefficient of variation (CV)0.0050548411
Kurtosis0.20268614
Mean37.454905
Median Absolute Deviation (MAD)0.11502099
Skewness0.072598962
Sum2771.663
Variance0.035845316
MonotonicityNot monotonic
2023-12-11T07:32:17.338272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.3076805687 3
 
2.4%
37.6973263442 2
 
1.6%
37.4340758697 2
 
1.6%
37.3365144934 2
 
1.6%
37.4809110636 2
 
1.6%
37.4124703998 1
 
0.8%
37.1384786317 1
 
0.8%
37.2995369265 1
 
0.8%
37.2092404384 1
 
0.8%
37.5454738542 1
 
0.8%
Other values (58) 58
46.0%
(Missing) 52
41.3%
ValueCountFrequency (%)
36.9577722927 1
0.8%
36.9869024301 1
0.8%
37.1304643221 1
0.8%
37.1384786317 1
0.8%
37.2092404384 1
0.8%
37.2199996554 1
0.8%
37.2592733806 1
0.8%
37.2594542897 1
0.8%
37.2843410666 1
0.8%
37.2995369265 1
0.8%
ValueCountFrequency (%)
37.9074152109 1
0.8%
37.904556138 1
0.8%
37.7591324429 1
0.8%
37.743800791 1
0.8%
37.7375945932 1
0.8%
37.7261400379 1
0.8%
37.7202668502 1
0.8%
37.7201781862 1
0.8%
37.7032295518 1
0.8%
37.6973263442 2
1.6%

WGS84경도
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct68
Distinct (%)91.9%
Missing52
Missing (%)41.3%
Infinite0
Infinite (%)0.0%
Mean126.98564
Minimum126.63134
Maximum127.68261
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2023-12-11T07:32:17.701184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.63134
5-th percentile126.74688
Q1126.80861
median126.93179
Q3127.11183
95-th percentile127.37782
Maximum127.68261
Range1.0512726
Interquartile range (IQR)0.30322866

Descriptive statistics

Standard deviation0.22524132
Coefficient of variation (CV)0.0017737542
Kurtosis1.3655084
Mean126.98564
Median Absolute Deviation (MAD)0.15248054
Skewness1.1572891
Sum9396.9375
Variance0.050733652
MonotonicityNot monotonic
2023-12-11T07:32:17.843498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126.8521091704 3
 
2.4%
126.7718945292 2
 
1.6%
126.9913190978 2
 
1.6%
126.8585106482 2
 
1.6%
126.7994028721 2
 
1.6%
126.9208617421 1
 
0.8%
127.0723454846 1
 
0.8%
127.6322639264 1
 
0.8%
127.6425308451 1
 
0.8%
127.6826086153 1
 
0.8%
Other values (58) 58
46.0%
(Missing) 52
41.3%
ValueCountFrequency (%)
126.631336059 1
0.8%
126.7229788379 1
0.8%
126.7366194052 1
0.8%
126.7411539774 1
0.8%
126.7499601616 1
0.8%
126.7506736993 1
0.8%
126.7529728585 1
0.8%
126.7645652387 1
0.8%
126.7710310369 1
0.8%
126.7718945292 2
1.6%
ValueCountFrequency (%)
127.6826086153 1
0.8%
127.6425308451 1
0.8%
127.6322639264 1
0.8%
127.4958260146 1
0.8%
127.3142740154 1
0.8%
127.3109571354 1
0.8%
127.242864633 1
0.8%
127.2256230217 1
0.8%
127.2237168768 1
0.8%
127.2193281315 1
0.8%

Interactions

2023-12-11T07:32:12.865186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:32:08.709064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:32:09.405464image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:32:09.992018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:32:10.630572image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:32:11.321270image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:32:12.257991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:32:12.951723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:32:08.806948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:32:09.497847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:32:10.096992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:32:10.733457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:32:11.434767image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:32:12.361589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:32:13.026418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:32:08.919045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:32:09.577951image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:32:10.185642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:32:10.828603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:32:11.522712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:32:12.465250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:32:13.107886image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:32:09.036001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:32:09.663580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:32:10.274276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:32:10.941917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:32:11.898575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:32:12.560386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:32:13.184645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:32:09.133451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:32:09.757952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:32:10.383492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:32:11.050146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:32:11.985653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:32:12.645694image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:32:13.253238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:32:09.216755image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:32:09.834848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:32:10.472710image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:32:11.140532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:32:12.061258image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:32:12.715839image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:32:13.323280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:32:09.302740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:32:09.911827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:32:10.549198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:32:11.236838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:32:12.157717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:32:12.785679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T07:32:17.954746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군명인허가일자영업상태명입소정원(명)자격소유인원수(명)총인원수(명)소재지도로명주소소재지우편번호WGS84위도WGS84경도
시군명1.0000.6420.0000.0000.1940.3651.0000.9800.9870.963
인허가일자0.6421.0000.6030.2950.0000.2060.9890.5840.4980.000
영업상태명0.0000.6031.0000.0000.0000.8740.0000.0000.0000.402
입소정원(명)0.0000.2950.0001.0000.5140.7810.9790.0730.0000.258
자격소유인원수(명)0.1940.0000.0000.5141.0000.5410.9790.4210.0000.558
총인원수(명)0.3650.2060.8740.7810.5411.0001.0000.3370.3130.560
소재지도로명주소1.0000.9890.0000.9790.9791.0001.0001.0001.0001.000
소재지우편번호0.9800.5840.0000.0730.4210.3371.0001.0000.9470.740
WGS84위도0.9870.4980.0000.0000.0000.3131.0000.9471.0000.520
WGS84경도0.9630.0000.4020.2580.5580.5601.0000.7400.5201.000
2023-12-11T07:32:18.063014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
영업상태명시군명
영업상태명1.0000.000
시군명0.0001.000
2023-12-11T07:32:18.142878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
인허가일자입소정원(명)자격소유인원수(명)총인원수(명)소재지우편번호WGS84위도WGS84경도시군명영업상태명
인허가일자1.000-0.2820.384-0.0130.250-0.190-0.1650.2560.451
입소정원(명)-0.2821.0000.0710.155-0.021-0.0380.1740.0000.000
자격소유인원수(명)0.3840.0711.0000.2240.151-0.172-0.2010.0410.000
총인원수(명)-0.0130.1550.2241.0000.043-0.134-0.1370.0460.674
소재지우편번호0.250-0.0210.1510.0431.000-0.8300.0690.7590.000
WGS84위도-0.190-0.038-0.172-0.134-0.8301.000-0.2180.7760.000
WGS84경도-0.1650.174-0.201-0.1370.069-0.2181.0000.7070.381
시군명0.2560.0000.0410.0460.7590.7760.7071.0000.000
영업상태명0.4510.0000.0000.6740.0000.0000.3810.0001.000

Missing values

2023-12-11T07:32:13.429675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T07:32:13.570618image/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.
2023-12-11T07:32:13.680820image/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

시군명사업장명인허가일자영업상태명입소정원(명)자격소유인원수(명)총인원수(명)소재지도로명주소소재지지번주소소재지우편번호WGS84위도WGS84경도
0고양시고양시장애인주간보호센터19980801운영중120028경기도 고양시 일산서구 고양대로672번길 15-7경기도 고양시 일산서구 일산동 627-4번지1035337.683567126.771031
1고양시고양시장애인종합복지관부설주간보호센터20040402운영중2034경기도 고양시 일산서구 탄현로 139경기도 고양시 일산서구 탄현동 111-1번지1023937.70323126.764565
2고양시원당주간보호센터20040302운영중2034경기도 고양시 덕양구 호국로 809경기도 고양시 덕양구 주교동 620-2번지1046237.658046126.837513
3고양시원당사회복지관 무지개장애인주간보호센터20070215운영중1504경기도 고양시 덕양구 호국로716번길 13-11경기도 고양시 덕양구 성사동 736-2번지1046937.651584126.832866
4고양시홀트장애인주간보호센터20030219운영중1834경기도 고양시 일산서구 탄현로 42경기도 고양시 일산서구 탄현동 41-1번지1024937.697326126.771895
5고양시고양시장애인부모회주간보호시설20010413운영중1734경기도 고양시 일산동구 강송로88번길 8-12경기도 고양시 일산동구 백석동 1167-4번지1044537.647421126.789737
6고양시기쁨터20040227운영중3034<NA>경기도 고양시 일산동구 식사동10324<NA><NA>
7고양시고양시덕양행신장애인주간보호센터20170118운영중30<NA><NA><NA>경기도 고양시 덕양구 행신동<NA><NA><NA>
8고양시홀트장애인주간보호시설20030219휴업 등1534경기도 고양시 일산서구 탄현로 42경기도 고양시 일산서구 탄현동 41-1번지1024937.697326126.771895
9과천시사랑의동산20060613운영중1543경기도 과천시 희망4길 57경기도 과천시 중앙동 17-4번지1380537.434076126.991319
시군명사업장명인허가일자영업상태명입소정원(명)자격소유인원수(명)총인원수(명)소재지도로명주소소재지지번주소소재지우편번호WGS84위도WGS84경도
116평택시합정장애인주간보호센터20031016운영중30030경기도 평택시 조개터로2번길 41경기도 평택시 합정동 936-3번지1791536.986902127.103108
117포천시포천시 장애인주간보호센터20131002운영중2036<NA>경기도 포천시 소흘읍 송우리<NA><NA><NA>
118포천시곰두리두레마을20041027운영중2100경기도 포천시 군내면 청성로 5경기도 포천시 군내면 하성북리 522-1번지1115137.904556127.211381
119하남시하남시장애인주간보호시설20001201운영중3006경기도 하남시 검단로19번길 27경기도 하남시 하산곡동 69-1번지1302437.523677127.223717
120화성시와~우리장애인주간보호센터20141231운영중2856<NA>경기도 화성시 봉담읍 동화리<NA><NA><NA>
121화성시와~우리 장애인주간보호센터20050820운영중2344경기도 화성시 봉담읍 와우안길 99경기도 화성시 봉담읍 동화리 197번지1829837.22126.973306
122화성시여울림장애인주간보호센터20170102운영중12<NA>3<NA>경기도 화성시 송산면 사강리<NA><NA><NA>
123화성시아르딤장애인주간보호센터20160121운영중16<NA>4<NA>경기도 화성시 팔탄면<NA><NA><NA>
124화성시좋은이웃장애인주간보호센터20100111운영중1644경기도 화성시 향남읍 행정서로3길 50경기도 화성시 향남읍 행정리 437-3번지1859837.130464126.919539
125화성시나래울 주간보호센터(나래울 복합복지타운)20110111운영중243<NA><NA>경기도 화성시 능동<NA><NA><NA>