Overview

Dataset statistics

Number of variables12
Number of observations31
Missing cells1
Missing cells (%)0.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.2 KiB
Average record size in memory107.3 B

Variable types

Numeric7
Text3
Categorical1
DateTime1

Dataset

Description부평구 장애인복지 신고시설 현황(소재지,대지규모,건물규모,운영주체 등)ex) 동수로 87 (부평동),4363.2,1458,손과손,39,39,1982-02-01,70,68,032-525-6043
Author인천광역시 부평구
URLhttps://data.incheon.go.kr/findData/publicDataDetail?dataId=3044744&srcSe=7661IVAWM27C61E190

Alerts

대지규모(제곱미터) is highly overall correlated with 건물규모(제곱미터) and 4 other fieldsHigh correlation
건물규모(제곱미터) is highly overall correlated with 대지규모(제곱미터) and 4 other fieldsHigh correlation
종사자수(정원) is highly overall correlated with 대지규모(제곱미터) and 4 other fieldsHigh correlation
종사자수(현원) is highly overall correlated with 대지규모(제곱미터) and 4 other fieldsHigh correlation
시설정원 is highly overall correlated with 대지규모(제곱미터) and 4 other fieldsHigh correlation
시설현원 is highly overall correlated with 대지규모(제곱미터) and 4 other fieldsHigh correlation
시설정원 has 1 (3.2%) missing valuesMissing
순번 has unique valuesUnique
시설명 has unique valuesUnique

Reproduction

Analysis started2024-03-18 04:01:36.159891
Analysis finished2024-03-18 04:01:41.564972
Duration5.41 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

UNIQUE 

Distinct31
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean16
Minimum1
Maximum31
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size411.0 B
2024-03-18T13:01:41.640377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.5
Q18.5
median16
Q323.5
95-th percentile29.5
Maximum31
Range30
Interquartile range (IQR)15

Descriptive statistics

Standard deviation9.0921211
Coefficient of variation (CV)0.56825757
Kurtosis-1.2
Mean16
Median Absolute Deviation (MAD)8
Skewness0
Sum496
Variance82.666667
MonotonicityStrictly increasing
2024-03-18T13:01:41.751865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
1 1
 
3.2%
2 1
 
3.2%
31 1
 
3.2%
30 1
 
3.2%
29 1
 
3.2%
28 1
 
3.2%
27 1
 
3.2%
26 1
 
3.2%
25 1
 
3.2%
24 1
 
3.2%
Other values (21) 21
67.7%
ValueCountFrequency (%)
1 1
3.2%
2 1
3.2%
3 1
3.2%
4 1
3.2%
5 1
3.2%
6 1
3.2%
7 1
3.2%
8 1
3.2%
9 1
3.2%
10 1
3.2%
ValueCountFrequency (%)
31 1
3.2%
30 1
3.2%
29 1
3.2%
28 1
3.2%
27 1
3.2%
26 1
3.2%
25 1
3.2%
24 1
3.2%
23 1
3.2%
22 1
3.2%

시설명
Text

UNIQUE 

Distinct31
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size380.0 B
2024-03-18T13:01:41.948613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length12
Mean length9.2580645
Min length3

Characters and Unicode

Total characters287
Distinct characters94
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique31 ?
Unique (%)100.0%

Sample

1st row예림원(지적)
2nd row은광원(지체/뇌병변)
3rd row성촌의집(지체/뇌병변)
4th row광명원(시각)
5th row성동원(청각/언어)
ValueCountFrequency (%)
부평장애인종합복지관 2
 
6.2%
성동주간보호센터 1
 
3.1%
스마트재활일터 1
 
3.1%
핸인핸부평 1
 
3.1%
아이드림 1
 
3.1%
송암보호작업장 1
 
3.1%
성동n 1
 
3.1%
굿프랜드 1
 
3.1%
꿈이룸장애인주간보호센터(뇌병변 1
 
3.1%
나래장애인주간보호센터 1
 
3.1%
Other values (21) 21
65.6%
2024-03-18T13:01:42.248022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
( 13
 
4.5%
) 13
 
4.5%
보 10
 
3.5%
호 10
 
3.5%
터 10
 
3.5%
원 9
 
3.1%
센 9
 
3.1%
간 8
 
2.8%
동 8
 
2.8%
주 8
 
2.8%
Other values (84) 189
65.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 249
86.8%
Open Punctuation 13
 
4.5%
Close Punctuation 13
 
4.5%
Decimal Number 5
 
1.7%
Other Punctuation 4
 
1.4%
Uppercase Letter 1
 
0.3%
Dash Punctuation 1
 
0.3%
Space Separator 1
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
보 10
 
4.0%
호 10
 
4.0%
터 10
 
4.0%
원 9
 
3.6%
센 9
 
3.6%
간 8
 
3.2%
동 8
 
3.2%
주 8
 
3.2%
인 8
 
3.2%
지 7
 
2.8%
Other values (73) 162
65.1%
Decimal Number
ValueCountFrequency (%)
5 1
20.0%
3 1
20.0%
2 1
20.0%
1 1
20.0%
4 1
20.0%
Open Punctuation
ValueCountFrequency (%)
( 13
100.0%
Close Punctuation
ValueCountFrequency (%)
) 13
100.0%
Other Punctuation
ValueCountFrequency (%)
/ 4
100.0%
Uppercase Letter
ValueCountFrequency (%)
N 1
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 249
86.8%
Common 37
 
12.9%
Latin 1
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
보 10
 
4.0%
호 10
 
4.0%
터 10
 
4.0%
원 9
 
3.6%
센 9
 
3.6%
간 8
 
3.2%
동 8
 
3.2%
주 8
 
3.2%
인 8
 
3.2%
지 7
 
2.8%
Other values (73) 162
65.1%
Common
ValueCountFrequency (%)
( 13
35.1%
) 13
35.1%
/ 4
 
10.8%
5 1
 
2.7%
3 1
 
2.7%
2 1
 
2.7%
1 1
 
2.7%
- 1
 
2.7%
1
 
2.7%
4 1
 
2.7%
Latin
ValueCountFrequency (%)
N 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 249
86.8%
ASCII 38
 
13.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
( 13
34.2%
) 13
34.2%
/ 4
 
10.5%
5 1
 
2.6%
N 1
 
2.6%
3 1
 
2.6%
2 1
 
2.6%
1 1
 
2.6%
- 1
 
2.6%
1
 
2.6%
Hangul
ValueCountFrequency (%)
보 10
 
4.0%
호 10
 
4.0%
터 10
 
4.0%
원 9
 
3.6%
센 9
 
3.6%
간 8
 
3.2%
동 8
 
3.2%
주 8
 
3.2%
인 8
 
3.2%
지 7
 
2.8%
Other values (73) 162
65.1%

소 재 지
Text

Distinct22
Distinct (%)71.0%
Missing0
Missing (%)0.0%
Memory size380.0 B
2024-03-18T13:01:42.449525image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length33
Median length27
Mean length20.032258
Min length11

Characters and Unicode

Total characters621
Distinct characters75
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

Unique16 ?
Unique (%)51.6%

Sample

1st row동수로 87 (부평동)
2nd row마분로 8 (부개동)
3rd row경인로 701번길 26 (십정동)
4th row경인로 769번길 27 (십정동)
5th row경인로 880 (부평동)
ValueCountFrequency (%)
경인로 8
 
6.8%
주공삼산타운 5
 
4.3%
산곡동 5
 
4.3%
체육관로 5
 
4.3%
111 5
 
4.3%
삼산동 5
 
4.3%
부평동 5
 
4.3%
십정동 5
 
4.3%
880 3
 
2.6%
일신동 3
 
2.6%
Other values (51) 68
58.1%
2024-03-18T13:01:42.773983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
86
 
13.8%
1 38
 
6.1%
동 33
 
5.3%
로 31
 
5.0%
) 31
 
5.0%
( 31
 
5.0%
, 23
 
3.7%
2 21
 
3.4%
산 17
 
2.7%
4 16
 
2.6%
Other values (65) 294
47.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 277
44.6%
Decimal Number 156
25.1%
Space Separator 86
 
13.8%
Other Punctuation 32
 
5.2%
Close Punctuation 31
 
5.0%
Open Punctuation 31
 
5.0%
Dash Punctuation 8
 
1.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 33
 
11.9%
로 31
 
11.2%
산 17
 
6.1%
부 12
 
4.3%
삼 10
 
3.6%
길 10
 
3.6%
번 10
 
3.6%
경 9
 
3.2%
평 9
 
3.2%
인 9
 
3.2%
Other values (48) 127
45.8%
Decimal Number
ValueCountFrequency (%)
1 38
24.4%
2 21
13.5%
4 16
10.3%
0 16
10.3%
3 13
 
8.3%
6 12
 
7.7%
7 11
 
7.1%
5 10
 
6.4%
8 10
 
6.4%
9 9
 
5.8%
Other Punctuation
ValueCountFrequency (%)
, 23
71.9%
@ 6
 
18.8%
/ 3
 
9.4%
Space Separator
ValueCountFrequency (%)
86
100.0%
Close Punctuation
ValueCountFrequency (%)
) 31
100.0%
Open Punctuation
ValueCountFrequency (%)
( 31
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 344
55.4%
Hangul 277
44.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 33
 
11.9%
로 31
 
11.2%
산 17
 
6.1%
부 12
 
4.3%
삼 10
 
3.6%
길 10
 
3.6%
번 10
 
3.6%
경 9
 
3.2%
평 9
 
3.2%
인 9
 
3.2%
Other values (48) 127
45.8%
Common
ValueCountFrequency (%)
86
25.0%
1 38
11.0%
) 31
 
9.0%
( 31
 
9.0%
, 23
 
6.7%
2 21
 
6.1%
4 16
 
4.7%
0 16
 
4.7%
3 13
 
3.8%
6 12
 
3.5%
Other values (7) 57
16.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 344
55.4%
Hangul 277
44.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
86
25.0%
1 38
11.0%
) 31
 
9.0%
( 31
 
9.0%
, 23
 
6.7%
2 21
 
6.1%
4 16
 
4.7%
0 16
 
4.7%
3 13
 
3.8%
6 12
 
3.5%
Other values (7) 57
16.6%
Hangul
ValueCountFrequency (%)
동 33
 
11.9%
로 31
 
11.2%
산 17
 
6.1%
부 12
 
4.3%
삼 10
 
3.6%
길 10
 
3.6%
번 10
 
3.6%
경 9
 
3.2%
평 9
 
3.2%
인 9
 
3.2%
Other values (48) 127
45.8%

대지규모(제곱미터)
Real number (ℝ)

HIGH CORRELATION 

Distinct27
Distinct (%)87.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1100.1497
Minimum53
Maximum7449.3
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size411.0 B
2024-03-18T13:01:42.894747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum53
5-th percentile54.5
Q1136.3
median282.6
Q3554.305
95-th percentile4589
Maximum7449.3
Range7396.3
Interquartile range (IQR)418.005

Descriptive statistics

Standard deviation1830.6603
Coefficient of variation (CV)1.6640102
Kurtosis4.1869426
Mean1100.1497
Median Absolute Deviation (MAD)198.6
Skewness2.1454158
Sum34104.64
Variance3351317
MonotonicityNot monotonic
2024-03-18T13:01:43.007951image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
66.0 3
 
9.7%
53.0 2
 
6.5%
144.0 2
 
6.5%
4363.2 1
 
3.2%
262.0 1
 
3.2%
147.4 1
 
3.2%
441.52 1
 
3.2%
447.0 1
 
3.2%
236.86 1
 
3.2%
517.61 1
 
3.2%
Other values (17) 17
54.8%
ValueCountFrequency (%)
53.0 2
6.5%
56.0 1
 
3.2%
66.0 3
9.7%
84.0 1
 
3.2%
128.6 1
 
3.2%
144.0 2
6.5%
147.4 1
 
3.2%
183.15 1
 
3.2%
204.2 1
 
3.2%
236.86 1
 
3.2%
ValueCountFrequency (%)
7449.3 1
3.2%
4716.0 1
3.2%
4462.0 1
3.2%
4363.2 1
3.2%
3074.0 1
3.2%
2241.3 1
3.2%
2241.0 1
3.2%
591.0 1
3.2%
517.61 1
3.2%
447.0 1
3.2%

건물규모(제곱미터)
Real number (ℝ)

HIGH CORRELATION 

Distinct27
Distinct (%)87.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean705.57871
Minimum53
Maximum3703
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size411.0 B
2024-03-18T13:01:43.123766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum53
5-th percentile54.5
Q177.44
median232.8
Q3709.785
95-th percentile3176
Maximum3703
Range3650
Interquartile range (IQR)632.345

Descriptive statistics

Standard deviation1021.7807
Coefficient of variation (CV)1.4481456
Kurtosis2.8859923
Mean705.57871
Median Absolute Deviation (MAD)176.8
Skewness1.9650748
Sum21872.94
Variance1044035.8
MonotonicityNot monotonic
2024-03-18T13:01:43.235503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
66.0 3
 
9.7%
53.0 2
 
6.5%
70.88 2
 
6.5%
1458.0 1
 
3.2%
149.83 1
 
3.2%
232.8 1
 
3.2%
441.52 1
 
3.2%
447.0 1
 
3.2%
236.86 1
 
3.2%
517.61 1
 
3.2%
Other values (17) 17
54.8%
ValueCountFrequency (%)
53.0 2
6.5%
56.0 1
 
3.2%
66.0 3
9.7%
70.88 2
6.5%
84.0 1
 
3.2%
121.64 1
 
3.2%
128.6 1
 
3.2%
134.09 1
 
3.2%
149.83 1
 
3.2%
183.15 1
 
3.2%
ValueCountFrequency (%)
3703.0 1
3.2%
3278.0 1
3.2%
3074.0 1
3.2%
2363.0 1
3.2%
1458.0 1
3.2%
1369.0 1
3.2%
898.44 1
3.2%
840.57 1
3.2%
579.0 1
3.2%
565.2 1
3.2%

운영주체
Categorical

Distinct12
Distinct (%)38.7%
Missing0
Missing (%)0.0%
Memory size380.0 B
손과손
7 
성촌재단
3 
성원
3 
개인
3 
송암복지재단
3 
Other values (7)
12 

Length

Max length13
Median length8
Mean length4.9677419
Min length2

Unique

Unique3 ?
Unique (%)9.7%

Sample

1st row손과손
2nd row은광복지재단
3rd row성촌재단
4th row광명복지재단
5th row성원

Common Values

ValueCountFrequency (%)
손과손 7
22.6%
성촌재단 3
9.7%
성원 3
9.7%
개인 3
9.7%
송암복지재단 3
9.7%
사)장애인부모회 3
9.7%
은광복지재단 2
 
6.5%
광명복지재단 2
 
6.5%
사)인천지적장애인복지협회 2
 
6.5%
베데스다복지재단 1
 
3.2%
Other values (2) 2
 
6.5%

Length

2024-03-18T13:01:43.360762image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
손과손 7
22.6%
성촌재단 3
9.7%
성원 3
9.7%
개인 3
9.7%
송암복지재단 3
9.7%
사)장애인부모회 3
9.7%
은광복지재단 2
 
6.5%
광명복지재단 2
 
6.5%
사)인천지적장애인복지협회 2
 
6.5%
베데스다복지재단 1
 
3.2%
Other values (2) 2
 
6.5%

종사자수(정원)
Real number (ℝ)

HIGH CORRELATION 

Distinct14
Distinct (%)45.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean10.096774
Minimum1
Maximum41
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size411.0 B
2024-03-18T13:01:43.469679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13.5
median5
Q37
95-th percentile35
Maximum41
Range40
Interquartile range (IQR)3.5

Descriptive statistics

Standard deviation11.973178
Coefficient of variation (CV)1.1858419
Kurtosis0.97714269
Mean10.096774
Median Absolute Deviation (MAD)2
Skewness1.5494041
Sum313
Variance143.35699
MonotonicityNot monotonic
2024-03-18T13:01:43.574827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
1 6
19.4%
6 5
16.1%
5 4
12.9%
4 4
12.9%
7 3
9.7%
41 1
 
3.2%
33 1
 
3.2%
27 1
 
3.2%
36 1
 
3.2%
18 1
 
3.2%
Other values (4) 4
12.9%
ValueCountFrequency (%)
1 6
19.4%
2 1
 
3.2%
3 1
 
3.2%
4 4
12.9%
5 4
12.9%
6 5
16.1%
7 3
9.7%
18 1
 
3.2%
26 1
 
3.2%
27 1
 
3.2%
ValueCountFrequency (%)
41 1
 
3.2%
36 1
 
3.2%
34 1
 
3.2%
33 1
 
3.2%
27 1
 
3.2%
26 1
 
3.2%
18 1
 
3.2%
7 3
9.7%
6 5
16.1%
5 4
12.9%

종사자수(현원)
Real number (ℝ)

HIGH CORRELATION 

Distinct14
Distinct (%)45.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9.7741935
Minimum1
Maximum40
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size411.0 B
2024-03-18T13:01:43.689389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13
median5
Q37
95-th percentile35
Maximum40
Range39
Interquartile range (IQR)4

Descriptive statistics

Standard deviation11.615248
Coefficient of variation (CV)1.1883587
Kurtosis1.3077792
Mean9.7741935
Median Absolute Deviation (MAD)2
Skewness1.6259475
Sum303
Variance134.91398
MonotonicityNot monotonic
2024-03-18T13:01:43.809659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
1 6
19.4%
6 5
16.1%
5 4
12.9%
7 3
9.7%
4 3
9.7%
3 2
 
6.5%
40 1
 
3.2%
33 1
 
3.2%
25 1
 
3.2%
36 1
 
3.2%
Other values (4) 4
12.9%
ValueCountFrequency (%)
1 6
19.4%
2 1
 
3.2%
3 2
 
6.5%
4 3
9.7%
5 4
12.9%
6 5
16.1%
7 3
9.7%
16 1
 
3.2%
22 1
 
3.2%
25 1
 
3.2%
ValueCountFrequency (%)
40 1
 
3.2%
36 1
 
3.2%
34 1
 
3.2%
33 1
 
3.2%
25 1
 
3.2%
22 1
 
3.2%
16 1
 
3.2%
7 3
9.7%
6 5
16.1%
5 4
12.9%

인가일
Date

Distinct30
Distinct (%)96.8%
Missing0
Missing (%)0.0%
Memory size380.0 B
Minimum1953-09-21 00:00:00
Maximum2021-12-10 00:00:00
2024-03-18T13:01:43.928643image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T13:01:44.058125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)

시설정원
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct15
Distinct (%)50.0%
Missing1
Missing (%)3.2%
Infinite0
Infinite (%)0.0%
Mean24.233333
Minimum4
Maximum74
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size411.0 B
2024-03-18T13:01:44.155009image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4
5-th percentile4
Q110
median15.5
Q331.5
95-th percentile70
Maximum74
Range70
Interquartile range (IQR)21.5

Descriptive statistics

Standard deviation20.58403
Coefficient of variation (CV)0.84940977
Kurtosis0.6668612
Mean24.233333
Median Absolute Deviation (MAD)11.5
Skewness1.172478
Sum727
Variance423.7023
MonotonicityNot monotonic
2024-03-18T13:01:44.252911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
4 7
22.6%
15 5
16.1%
30 4
12.9%
70 2
 
6.5%
10 2
 
6.5%
74 1
 
3.2%
35 1
 
3.2%
50 1
 
3.2%
32 1
 
3.2%
11 1
 
3.2%
Other values (5) 5
16.1%
ValueCountFrequency (%)
4 7
22.6%
10 2
 
6.5%
11 1
 
3.2%
15 5
16.1%
16 1
 
3.2%
20 1
 
3.2%
21 1
 
3.2%
30 4
12.9%
32 1
 
3.2%
35 1
 
3.2%
ValueCountFrequency (%)
74 1
 
3.2%
70 2
6.5%
50 1
 
3.2%
45 1
 
3.2%
40 1
 
3.2%
35 1
 
3.2%
32 1
 
3.2%
30 4
12.9%
21 1
 
3.2%
20 1
 
3.2%

시설현원
Real number (ℝ)

HIGH CORRELATION 

Distinct20
Distinct (%)64.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean23.806452
Minimum2
Maximum166
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size411.0 B
2024-03-18T13:01:44.350821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile4
Q18.5
median14
Q330
95-th percentile51.5
Maximum166
Range164
Interquartile range (IQR)21.5

Descriptive statistics

Standard deviation30.152302
Coefficient of variation (CV)1.2665601
Kurtosis16.975517
Mean23.806452
Median Absolute Deviation (MAD)10
Skewness3.7184794
Sum738
Variance909.16129
MonotonicityNot monotonic
2024-03-18T13:01:44.455545image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
4 6
19.4%
30 3
 
9.7%
10 3
 
9.7%
29 2
 
6.5%
12 2
 
6.5%
58 1
 
3.2%
14 1
 
3.2%
25 1
 
3.2%
35 1
 
3.2%
45 1
 
3.2%
Other values (10) 10
32.3%
ValueCountFrequency (%)
2 1
 
3.2%
4 6
19.4%
7 1
 
3.2%
10 3
9.7%
11 1
 
3.2%
12 2
 
6.5%
13 1
 
3.2%
14 1
 
3.2%
15 1
 
3.2%
17 1
 
3.2%
ValueCountFrequency (%)
166 1
 
3.2%
58 1
 
3.2%
45 1
 
3.2%
43 1
 
3.2%
41 1
 
3.2%
35 1
 
3.2%
30 3
9.7%
29 2
6.5%
25 1
 
3.2%
20 1
 
3.2%

전화번호
Text

Distinct25
Distinct (%)80.6%
Missing0
Missing (%)0.0%
Memory size380.0 B
2024-03-18T13:01:44.618605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.032258
Min length12

Characters and Unicode

Total characters373
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

Unique23 ?
Unique (%)74.2%

Sample

1st row032-525-6043
2nd row032-501-0105
3rd row032-422-0573
4th row032-514-1956
5th row032-522-2984
ValueCountFrequency (%)
032-525-6043 6
 
19.4%
032-506-6596 2
 
6.5%
032-330-1307 1
 
3.2%
032-517-0630 1
 
3.2%
032-715-4775 1
 
3.2%
032-528-0337 1
 
3.2%
032-508-3773 1
 
3.2%
032-528-8863 1
 
3.2%
032-506-7746 1
 
3.2%
032-428-1741 1
 
3.2%
Other values (15) 15
48.4%
2024-03-18T13:01:44.900286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 62
16.6%
0 61
16.4%
2 53
14.2%
3 52
13.9%
5 44
11.8%
6 22
 
5.9%
7 20
 
5.4%
1 19
 
5.1%
4 16
 
4.3%
9 14
 
3.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 311
83.4%
Dash Punctuation 62
 
16.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 61
19.6%
2 53
17.0%
3 52
16.7%
5 44
14.1%
6 22
 
7.1%
7 20
 
6.4%
1 19
 
6.1%
4 16
 
5.1%
9 14
 
4.5%
8 10
 
3.2%
Dash Punctuation
ValueCountFrequency (%)
- 62
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 373
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 62
16.6%
0 61
16.4%
2 53
14.2%
3 52
13.9%
5 44
11.8%
6 22
 
5.9%
7 20
 
5.4%
1 19
 
5.1%
4 16
 
4.3%
9 14
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 373
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 62
16.6%
0 61
16.4%
2 53
14.2%
3 52
13.9%
5 44
11.8%
6 22
 
5.9%
7 20
 
5.4%
1 19
 
5.1%
4 16
 
4.3%
9 14
 
3.8%

Interactions

2024-03-18T13:01:40.456192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T13:01:36.588414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T13:01:37.475872image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T13:01:38.045422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T13:01:38.652802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T13:01:39.284304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T13:01:39.916259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T13:01:40.537442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T13:01:36.929920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T13:01:37.554655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T13:01:38.116952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T13:01:38.758240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T13:01:39.366848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T13:01:40.000733image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T13:01:40.625076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T13:01:37.016257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T13:01:37.639005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T13:01:38.198807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T13:01:38.842368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T13:01:39.459106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T13:01:40.073813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T13:01:40.714675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T13:01:37.101342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T13:01:37.739913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T13:01:38.282607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T13:01:38.934849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T13:01:39.556252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T13:01:40.144607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T13:01:40.796080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T13:01:37.195931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T13:01:37.818078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T13:01:38.388014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T13:01:39.012767image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T13:01:39.646330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T13:01:40.223134image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T13:01:40.880703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T13:01:37.284912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T13:01:37.898814image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T13:01:38.477137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T13:01:39.098798image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T13:01:39.735412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T13:01:40.297107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T13:01:40.963096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T13:01:37.379832image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T13:01:37.972126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T13:01:38.558926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T13:01:39.206088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T13:01:39.821305image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T13:01:40.370490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-18T13:01:45.009979image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번시설명소 재 지대지규모(제곱미터)건물규모(제곱미터)운영주체종사자수(정원)종사자수(현원)인가일시설정원시설현원전화번호
순번1.0001.0000.0000.3820.6320.5680.4380.4380.9450.7930.6930.839
시설명1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
소 재 지0.0001.0001.0000.0000.0001.0000.0000.0001.0000.0000.0000.570
대지규모(제곱미터)0.3821.0000.0001.0000.8740.6420.8740.8320.7400.7320.6720.941
건물규모(제곱미터)0.6321.0000.0000.8741.0000.0000.9620.9430.0000.8150.8120.955
운영주체0.5681.0001.0000.6420.0001.0000.3570.0001.0000.7970.0001.000
종사자수(정원)0.4381.0000.0000.8740.9620.3571.0000.9950.8030.8610.8160.815
종사자수(현원)0.4381.0000.0000.8320.9430.0000.9951.0000.9090.8610.7840.815
인가일0.9451.0001.0000.7400.0001.0000.8030.9091.0001.0000.0000.953
시설정원0.7931.0000.0000.7320.8150.7970.8610.8611.0001.0000.9710.994
시설현원0.6931.0000.0000.6720.8120.0000.8160.7840.0000.9711.0000.357
전화번호0.8391.0000.5700.9410.9551.0000.8150.8150.9530.9940.3571.000
2024-03-18T13:01:45.138520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번대지규모(제곱미터)건물규모(제곱미터)종사자수(정원)종사자수(현원)시설정원시설현원운영주체
순번1.000-0.055-0.064-0.157-0.156-0.0610.0860.169
대지규모(제곱미터)-0.0551.0000.9450.8700.8690.8890.8670.242
건물규모(제곱미터)-0.0640.9451.0000.8770.8750.9330.8990.000
종사자수(정원)-0.1570.8700.8771.0000.9990.8990.8840.172
종사자수(현원)-0.1560.8690.8750.9991.0000.8990.8870.000
시설정원-0.0610.8890.9330.8990.8991.0000.9440.300
시설현원0.0860.8670.8990.8840.8870.9441.0000.000
운영주체0.1690.2420.0000.1720.0000.3000.0001.000

Missing values

2024-03-18T13:01:41.356209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-18T13:01:41.502926image/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

순번시설명소 재 지대지규모(제곱미터)건물규모(제곱미터)운영주체종사자수(정원)종사자수(현원)인가일시설정원시설현원전화번호
01예림원(지적)동수로 87 (부평동)4363.21458.0손과손41401982-02-017058032-525-6043
12은광원(지체/뇌병변)마분로 8 (부개동)3074.02363.0은광복지재단33331976-06-017441032-501-0105
23성촌의집(지체/뇌병변)경인로 701번길 26 (십정동)4716.03074.0성촌재단27251957-06-173529032-422-0573
34광명원(시각)경인로 769번길 27 (십정동)7449.33278.0광명복지재단36361958-01-077043032-514-1956
45성동원(청각/언어)경인로 880 (부평동)2241.01369.0성원18161953-09-215017032-522-2984
56우리들의집(지적-실비)경인로 701번길 26 (십정동)290.38898.44성촌재단26222006-12-143229032-433-7907
67쉴만한물가의집원적로 421번길 9-12 (산곡동)204.2121.64개인552010-12-311010032-277-9595
78예림원공동생활가정(1)체육관로 111, 411/1505 (삼산동, 주공삼산타운@)53.053.0손과손111997-08-0144032-525-6043
89예림원공동생활가정(2)체육관로 111, 415/1406 (삼산동, 주공삼산타운@)66.066.0손과손112001-07-2144032-525-6043
910예림원공동생활가정(3)체육관로 111, 412/906 (삼산동, 주공삼산타운@)53.053.0손과손112002-03-0844032-525-6043
순번시설명소 재 지대지규모(제곱미터)건물규모(제곱미터)운영주체종사자수(정원)종사자수(현원)인가일시설정원시설현원전화번호
2122부흥장애인주간보호센터부흥로 334번길 37, 3층 (부평동,봉담빌딩)183.15183.15베데스다복지재단432012-12-21157070-7562-9125
2223나래장애인주간보호센터부영로 161, 4층 402호 (산곡동,주안빌딩)377.12377.12주안복지재단772015-04-072020032-513-9300
2324꿈이룸장애인주간보호센터(뇌병변)안남로 62, 3층(부평동,한솔상가)331.0188.75사)장애인부모회552017-11-011512032-508-6974
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