Overview

Dataset statistics

Number of variables15
Number of observations32
Missing cells97
Missing cells (%)20.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.1 KiB
Average record size in memory132.1 B

Variable types

Categorical3
Text3
Numeric8
DateTime1

Dataset

Description광주광역시 사회복지 이용시설에 관한 정보로 사회복지시설(노인,장애인, 정신지체 등)의 시설현황을 제공합니다.
Author광주광역시
URLhttps://www.data.go.kr/data/15043857/fileData.do

Alerts

형태 has constant value ""Constant
데이터기준일자 has constant value ""Constant
대상자 is highly overall correlated with 정원 and 3 other fieldsHigh correlation
시설종류 is highly overall correlated with 정원 and 2 other fieldsHigh correlation
시설수 is highly overall correlated with 정원 and 5 other fieldsHigh correlation
정원 is highly overall correlated with 시설수 and 8 other fieldsHigh correlation
현원 is highly overall correlated with 정원 and 3 other fieldsHigh correlation
종사자수 is highly overall correlated with 시설수 and 7 other fieldsHigh correlation
동구시설분포현황 is highly overall correlated with 시설수 and 5 other fieldsHigh correlation
서구시설분포현황 is highly overall correlated with 시설수 and 5 other fieldsHigh correlation
북구시설분포현황 is highly overall correlated with 시설수 and 5 other fieldsHigh correlation
광산구시설분포현황 is highly overall correlated with 시설수 and 5 other fieldsHigh correlation
유형 has 13 (40.6%) missing valuesMissing
정원 has 25 (78.1%) missing valuesMissing
현원 has 16 (50.0%) missing valuesMissing
종사자수 has 1 (3.1%) missing valuesMissing
동구시설분포현황 has 10 (31.2%) missing valuesMissing
서구시설분포현황 has 11 (34.4%) missing valuesMissing
남구시설분포현황 has 6 (18.8%) missing valuesMissing
북구시설분포현황 has 7 (21.9%) missing valuesMissing
광산구시설분포현황 has 8 (25.0%) missing valuesMissing

Reproduction

Analysis started2023-12-12 14:59:25.864537
Analysis finished2023-12-12 14:59:33.328253
Duration7.46 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

대상자
Categorical

HIGH CORRELATION 

Distinct8
Distinct (%)25.0%
Missing0
Missing (%)0.0%
Memory size388.0 B
노인
9 
장애인
8 
아동
6 
기타
5 
정신질환자
1 
Other values (3)
3 

Length

Max length5
Median length2
Mean length2.53125
Min length2

Unique

Unique4 ?
Unique (%)12.5%

Sample

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

Common Values

ValueCountFrequency (%)
노인 9
28.1%
장애인 8
25.0%
아동 6
18.8%
기타 5
15.6%
정신질환자 1
 
3.1%
노숙인 등 1
 
3.1%
지역주민 1
 
3.1%
영유아 1
 
3.1%

Length

2023-12-12T23:59:33.418948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T23:59:33.584599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
노인 9
27.3%
장애인 8
24.2%
아동 6
18.2%
기타 5
15.2%
정신질환자 1
 
3.0%
노숙인 1
 
3.0%
등 1
 
3.0%
지역주민 1
 
3.0%
영유아 1
 
3.0%

시설종류
Categorical

HIGH CORRELATION 

Distinct12
Distinct (%)37.5%
Missing0
Missing (%)0.0%
Memory size388.0 B
노인복지시설
9 
장애인복지시설
8 
아동복지시설
6 
정신보건시설
1 
지역자활센터
1 
Other values (7)
7 

Length

Max length9
Median length6
Mean length6.34375
Min length4

Unique

Unique9 ?
Unique (%)28.1%

Sample

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

Common Values

ValueCountFrequency (%)
노인복지시설 9
28.1%
장애인복지시설 8
25.0%
아동복지시설 6
18.8%
정신보건시설 1
 
3.1%
지역자활센터 1
 
3.1%
노숙인시설 1
 
3.1%
사회복지관 1
 
3.1%
어린이집 1
 
3.1%
정신보건센터 1
 
3.1%
중독관리지원센터 1
 
3.1%
Other values (2) 2
 
6.2%

Length

2023-12-12T23:59:33.765289image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
노인복지시설 9
28.1%
장애인복지시설 8
25.0%
아동복지시설 6
18.8%
정신보건시설 1
 
3.1%
지역자활센터 1
 
3.1%
노숙인시설 1
 
3.1%
사회복지관 1
 
3.1%
어린이집 1
 
3.1%
정신보건센터 1
 
3.1%
중독관리지원센터 1
 
3.1%
Other values (2) 2
 
6.2%

형태
Categorical

CONSTANT 

Distinct1
Distinct (%)3.1%
Missing0
Missing (%)0.0%
Memory size388.0 B
이용시설
32 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
이용시설 32
100.0%

Length

2023-12-12T23:59:33.953768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T23:59:34.085045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
이용시설 32
100.0%

세부종류
Text

Distinct22
Distinct (%)68.8%
Missing0
Missing (%)0.0%
Memory size388.0 B
2023-12-12T23:59:34.282547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length11
Mean length8.25
Min length4

Characters and Unicode

Total characters264
Distinct characters63
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

Unique18 ?
Unique (%)56.2%

Sample

1st row재가노인복지시설
2nd row재가노인복지시설
3rd row재가노인복지시설
4th row재가노인복지시설
5th row노인여가복지시설
ValueCountFrequency (%)
장애인지역사회재활시설 5
 
14.7%
재가노인복지시설 4
 
11.8%
노인여가복지시설 3
 
8.8%
장애인직업재활시설 2
 
5.9%
다함께돌봄센터 1
 
2.9%
지역아동센터 1
 
2.9%
치매통합관리센터 1
 
2.9%
중독관리지원센터 1
 
2.9%
정신보건센터 1
 
2.9%
어린이집 1
 
2.9%
Other values (14) 14
41.2%
2023-12-12T23:59:34.644516image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
시 20
 
7.6%
지 19
 
7.2%
설 19
 
7.2%
인 18
 
6.8%
재 12
 
4.5%
노 10
 
3.8%
활 9
 
3.4%
가 9
 
3.4%
장 8
 
3.0%
애 8
 
3.0%
Other values (53) 132
50.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 262
99.2%
Space Separator 2
 
0.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 20
 
7.6%
지 19
 
7.3%
설 19
 
7.3%
인 18
 
6.9%
재 12
 
4.6%
노 10
 
3.8%
활 9
 
3.4%
가 9
 
3.4%
장 8
 
3.1%
애 8
 
3.1%
Other values (52) 130
49.6%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 262
99.2%
Common 2
 
0.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 20
 
7.6%
지 19
 
7.3%
설 19
 
7.3%
인 18
 
6.9%
재 12
 
4.6%
노 10
 
3.8%
활 9
 
3.4%
가 9
 
3.4%
장 8
 
3.1%
애 8
 
3.1%
Other values (52) 130
49.6%
Common
ValueCountFrequency (%)
2
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 262
99.2%
ASCII 2
 
0.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
시 20
 
7.6%
지 19
 
7.3%
설 19
 
7.3%
인 18
 
6.9%
재 12
 
4.6%
노 10
 
3.8%
활 9
 
3.4%
가 9
 
3.4%
장 8
 
3.1%
애 8
 
3.1%
Other values (52) 130
49.6%
ASCII
ValueCountFrequency (%)
2
100.0%

유형
Text

MISSING 

Distinct19
Distinct (%)100.0%
Missing13
Missing (%)40.6%
Memory size388.0 B
2023-12-12T23:59:34.870064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length10
Mean length8.1578947
Min length3

Characters and Unicode

Total characters155
Distinct characters72
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

Unique19 ?
Unique (%)100.0%

Sample

1st row방문요양
2nd row주야간보호
3rd row방문목욕
4th row재가노인지원
5th row노인복지관
ValueCountFrequency (%)
방문요양 1
 
4.8%
장애인보호작업장 1
 
4.8%
건강가정다문화가족지원센터(여성가족부 1
 
4.8%
장애인생활이동지원센터 1
 
4.8%
치매안심센터 1
 
4.8%
중독관리통합지원센터 1
 
4.8%
기초정신건강복지센터 1
 
4.8%
재활훈련시설(주간재활시설 1
 
4.8%
정신질환자 1
 
4.8%
장애인근로사업장 1
 
4.8%
Other values (11) 11
52.4%
2023-12-12T23:59:35.323954image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
인 9
 
5.8%
장 8
 
5.2%
지 7
 
4.5%
터 6
 
3.9%
애 6
 
3.9%
센 6
 
3.9%
가 4
 
2.6%
원 4
 
2.6%
관 4
 
2.6%
설 4
 
2.6%
Other values (62) 97
62.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 149
96.1%
Space Separator 2
 
1.3%
Open Punctuation 2
 
1.3%
Close Punctuation 2
 
1.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
인 9
 
6.0%
장 8
 
5.4%
지 7
 
4.7%
터 6
 
4.0%
애 6
 
4.0%
센 6
 
4.0%
가 4
 
2.7%
원 4
 
2.7%
관 4
 
2.7%
설 4
 
2.7%
Other values (59) 91
61.1%
Space Separator
ValueCountFrequency (%)
2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 149
96.1%
Common 6
 
3.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
인 9
 
6.0%
장 8
 
5.4%
지 7
 
4.7%
터 6
 
4.0%
애 6
 
4.0%
센 6
 
4.0%
가 4
 
2.7%
원 4
 
2.7%
관 4
 
2.7%
설 4
 
2.7%
Other values (59) 91
61.1%
Common
ValueCountFrequency (%)
2
33.3%
( 2
33.3%
) 2
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 149
96.1%
ASCII 6
 
3.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
인 9
 
6.0%
장 8
 
5.4%
지 7
 
4.7%
터 6
 
4.0%
애 6
 
4.0%
센 6
 
4.0%
가 4
 
2.7%
원 4
 
2.7%
관 4
 
2.7%
설 4
 
2.7%
Other values (59) 91
61.1%
ASCII
ValueCountFrequency (%)
2
33.3%
( 2
33.3%
) 2
33.3%

시설수
Real number (ℝ)

HIGH CORRELATION 

Distinct16
Distinct (%)50.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean97.40625
Minimum1
Maximum1313
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size420.0 B
2023-12-12T23:59:35.472288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median5
Q327.5
95-th percentile651.25
Maximum1313
Range1312
Interquartile range (IQR)26.5

Descriptive statistics

Standard deviation294.28205
Coefficient of variation (CV)3.0211824
Kurtosis12.814953
Mean97.40625
Median Absolute Deviation (MAD)4
Skewness3.6613103
Sum3117
Variance86601.926
MonotonicityNot monotonic
2023-12-12T23:59:35.597444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
1 9
28.1%
5 7
21.9%
9 2
 
6.2%
7 2
 
6.2%
38 1
 
3.1%
1072 1
 
3.1%
2 1
 
3.1%
307 1
 
3.1%
20 1
 
3.1%
24 1
 
3.1%
Other values (6) 6
18.8%
ValueCountFrequency (%)
1 9
28.1%
2 1
 
3.1%
5 7
21.9%
7 2
 
6.2%
9 2
 
6.2%
11 1
 
3.1%
20 1
 
3.1%
24 1
 
3.1%
38 1
 
3.1%
44 1
 
3.1%
ValueCountFrequency (%)
1313 1
3.1%
1072 1
3.1%
307 1
3.1%
98 1
3.1%
62 1
3.1%
50 1
3.1%
44 1
3.1%
38 1
3.1%
24 1
3.1%
20 1
3.1%

정원
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct7
Distinct (%)100.0%
Missing25
Missing (%)78.1%
Infinite0
Infinite (%)0.0%
Mean9334.7143
Minimum5
Maximum55020
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size420.0 B
2023-12-12T23:59:35.691545image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5
5-th percentile52.4
Q1224
median720
Q34575
95-th percentile41038.8
Maximum55020
Range55015
Interquartile range (IQR)4351

Descriptive statistics

Standard deviation20368.424
Coefficient of variation (CV)2.1820083
Kurtosis6.4985691
Mean9334.7143
Median Absolute Deviation (MAD)557
Skewness2.5334603
Sum65343
Variance4.148727 × 108
MonotonicityNot monotonic
2023-12-12T23:59:35.781292image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
734 1
 
3.1%
720 1
 
3.1%
285 1
 
3.1%
163 1
 
3.1%
5 1
 
3.1%
8416 1
 
3.1%
55020 1
 
3.1%
(Missing) 25
78.1%
ValueCountFrequency (%)
5 1
3.1%
163 1
3.1%
285 1
3.1%
720 1
3.1%
734 1
3.1%
8416 1
3.1%
55020 1
3.1%
ValueCountFrequency (%)
55020 1
3.1%
8416 1
3.1%
734 1
3.1%
720 1
3.1%
285 1
3.1%
163 1
3.1%
5 1
3.1%

현원
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct16
Distinct (%)100.0%
Missing16
Missing (%)50.0%
Infinite0
Infinite (%)0.0%
Mean3995
Minimum100
Maximum36742
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size420.0 B
2023-12-12T23:59:35.891197image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum100
5-th percentile151
Q1270.25
median691
Q31815.75
95-th percentile16330.75
Maximum36742
Range36642
Interquartile range (IQR)1545.5

Descriptive statistics

Standard deviation9145.7835
Coefficient of variation (CV)2.2893075
Kurtosis12.706577
Mean3995
Median Absolute Deviation (MAD)557
Skewness3.4711255
Sum63920
Variance83645355
MonotonicityNot monotonic
2023-12-12T23:59:36.026273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
199 1
 
3.1%
9527 1
 
3.1%
1361 1
 
3.1%
1517 1
 
3.1%
36742 1
 
3.1%
7518 1
 
3.1%
168 1
 
3.1%
1799 1
 
3.1%
674 1
 
3.1%
100 1
 
3.1%
Other values (6) 6
 
18.8%
(Missing) 16
50.0%
ValueCountFrequency (%)
100 1
3.1%
168 1
3.1%
199 1
3.1%
250 1
3.1%
277 1
3.1%
589 1
3.1%
625 1
3.1%
674 1
3.1%
708 1
3.1%
1361 1
3.1%
ValueCountFrequency (%)
36742 1
3.1%
9527 1
3.1%
7518 1
3.1%
1866 1
3.1%
1799 1
3.1%
1517 1
3.1%
1361 1
3.1%
708 1
3.1%
674 1
3.1%
625 1
3.1%

종사자수
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct28
Distinct (%)90.3%
Missing1
Missing (%)3.1%
Infinite0
Infinite (%)0.0%
Mean399.22581
Minimum1
Maximum7498
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size420.0 B
2023-12-12T23:59:36.170523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q114.5
median57
Q3176.5
95-th percentile1202
Maximum7498
Range7497
Interquartile range (IQR)162

Descriptive statistics

Standard deviation1357.0929
Coefficient of variation (CV)3.3993115
Kurtosis27.204375
Mean399.22581
Median Absolute Deviation (MAD)47
Skewness5.1177475
Sum12376
Variance1841701.1
MonotonicityNot monotonic
2023-12-12T23:59:36.310925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
221 2
 
6.2%
88 2
 
6.2%
2 2
 
6.2%
1721 1
 
3.1%
76 1
 
3.1%
45 1
 
3.1%
94 1
 
3.1%
52 1
 
3.1%
7498 1
 
3.1%
10 1
 
3.1%
Other values (18) 18
56.2%
ValueCountFrequency (%)
1 1
3.1%
2 2
6.2%
6 1
3.1%
7 1
3.1%
10 1
3.1%
11 1
3.1%
14 1
3.1%
15 1
3.1%
21 1
3.1%
25 1
3.1%
ValueCountFrequency (%)
7498 1
3.1%
1721 1
3.1%
683 1
3.1%
446 1
3.1%
341 1
3.1%
221 2
6.2%
183 1
3.1%
170 1
3.1%
147 1
3.1%
94 1
3.1%

동구시설분포현황
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct8
Distinct (%)36.4%
Missing10
Missing (%)31.2%
Infinite0
Infinite (%)0.0%
Mean10.272727
Minimum1
Maximum109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size420.0 B
2023-12-12T23:59:36.435393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q34.5
95-th percentile55.2
Maximum109
Range108
Interquartile range (IQR)3.5

Descriptive statistics

Standard deviation25.245805
Coefficient of variation (CV)2.4575562
Kurtosis12.111005
Mean10.272727
Median Absolute Deviation (MAD)0
Skewness3.4305212
Sum226
Variance637.35065
MonotonicityNot monotonic
2023-12-12T23:59:36.538769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
1 12
37.5%
6 2
 
6.2%
2 2
 
6.2%
3 2
 
6.2%
5 1
 
3.1%
109 1
 
3.1%
21 1
 
3.1%
57 1
 
3.1%
(Missing) 10
31.2%
ValueCountFrequency (%)
1 12
37.5%
2 2
 
6.2%
3 2
 
6.2%
5 1
 
3.1%
6 2
 
6.2%
21 1
 
3.1%
57 1
 
3.1%
109 1
 
3.1%
ValueCountFrequency (%)
109 1
 
3.1%
57 1
 
3.1%
21 1
 
3.1%
6 2
 
6.2%
5 1
 
3.1%
3 2
 
6.2%
2 2
 
6.2%
1 12
37.5%

서구시설분포현황
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct11
Distinct (%)52.4%
Missing11
Missing (%)34.4%
Infinite0
Infinite (%)0.0%
Mean27.142857
Minimum1
Maximum230
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size420.0 B
2023-12-12T23:59:36.657105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median3
Q39
95-th percentile210
Maximum230
Range229
Interquartile range (IQR)8

Descriptive statistics

Standard deviation65.077097
Coefficient of variation (CV)2.3975773
Kurtosis7.1018022
Mean27.142857
Median Absolute Deviation (MAD)2
Skewness2.8541602
Sum570
Variance4235.0286
MonotonicityNot monotonic
2023-12-12T23:59:36.761415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
1 9
28.1%
9 2
 
6.2%
3 2
 
6.2%
19 1
 
3.1%
15 1
 
3.1%
230 1
 
3.1%
8 1
 
3.1%
2 1
 
3.1%
5 1
 
3.1%
48 1
 
3.1%
(Missing) 11
34.4%
ValueCountFrequency (%)
1 9
28.1%
2 1
 
3.1%
3 2
 
6.2%
5 1
 
3.1%
8 1
 
3.1%
9 2
 
6.2%
15 1
 
3.1%
19 1
 
3.1%
48 1
 
3.1%
210 1
 
3.1%
ValueCountFrequency (%)
230 1
3.1%
210 1
3.1%
48 1
3.1%
19 1
3.1%
15 1
3.1%
9 2
6.2%
8 1
3.1%
5 1
3.1%
3 2
6.2%
2 1
3.1%

남구시설분포현황
Text

MISSING 

Distinct13
Distinct (%)50.0%
Missing6
Missing (%)18.8%
Memory size388.0 B
2023-12-12T23:59:36.844204image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length1
Mean length1.3461538
Min length1

Characters and Unicode

Total characters35
Distinct characters10
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

Unique11 ?
Unique (%)42.3%

Sample

1st row28
2nd row13
3rd row16
4th row3
5th row3
ValueCountFrequency (%)
1 12
48.0%
3 3
 
12.0%
28 1
 
4.0%
13 1
 
4.0%
16 1
 
4.0%
227 1
 
4.0%
5 1
 
4.0%
2 1
 
4.0%
8 1
 
4.0%
4 1
 
4.0%
Other values (2) 2
 
8.0%
2023-12-12T23:59:37.072786image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 15
42.9%
3 5
 
14.3%
2 4
 
11.4%
8 2
 
5.7%
6 2
 
5.7%
2
 
5.7%
4 2
 
5.7%
7 1
 
2.9%
5 1
 
2.9%
9 1
 
2.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 33
94.3%
Space Separator 2
 
5.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 15
45.5%
3 5
 
15.2%
2 4
 
12.1%
8 2
 
6.1%
6 2
 
6.1%
4 2
 
6.1%
7 1
 
3.0%
5 1
 
3.0%
9 1
 
3.0%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 35
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 15
42.9%
3 5
 
14.3%
2 4
 
11.4%
8 2
 
5.7%
6 2
 
5.7%
2
 
5.7%
4 2
 
5.7%
7 1
 
2.9%
5 1
 
2.9%
9 1
 
2.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 35
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 15
42.9%
3 5
 
14.3%
2 4
 
11.4%
8 2
 
5.7%
6 2
 
5.7%
2
 
5.7%
4 2
 
5.7%
7 1
 
2.9%
5 1
 
2.9%
9 1
 
2.9%

북구시설분포현황
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct14
Distinct (%)56.0%
Missing7
Missing (%)21.9%
Infinite0
Infinite (%)0.0%
Mean35.68
Minimum1
Maximum379
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size420.0 B
2023-12-12T23:59:37.185077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median2
Q310
95-th percentile257.2
Maximum379
Range378
Interquartile range (IQR)9

Descriptive statistics

Standard deviation94.013616
Coefficient of variation (CV)2.6349108
Kurtosis9.1088092
Mean35.68
Median Absolute Deviation (MAD)1
Skewness3.1151911
Sum892
Variance8838.56
MonotonicityNot monotonic
2023-12-12T23:59:37.643740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
1 10
31.2%
2 3
 
9.4%
17 1
 
3.1%
10 1
 
3.1%
11 1
 
3.1%
4 1
 
3.1%
379 1
 
3.1%
20 1
 
3.1%
9 1
 
3.1%
6 1
 
3.1%
Other values (4) 4
 
12.5%
(Missing) 7
21.9%
ValueCountFrequency (%)
1 10
31.2%
2 3
 
9.4%
3 1
 
3.1%
4 1
 
3.1%
6 1
 
3.1%
7 1
 
3.1%
9 1
 
3.1%
10 1
 
3.1%
11 1
 
3.1%
17 1
 
3.1%
ValueCountFrequency (%)
379 1
3.1%
292 1
3.1%
118 1
3.1%
20 1
3.1%
17 1
3.1%
11 1
3.1%
10 1
3.1%
9 1
3.1%
7 1
3.1%
6 1
3.1%

광산구시설분포현황
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct10
Distinct (%)41.7%
Missing8
Missing (%)25.0%
Infinite0
Infinite (%)0.0%
Mean38.25
Minimum1
Maximum377
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size420.0 B
2023-12-12T23:59:37.745873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median2
Q310
95-th percentile323.45
Maximum377
Range376
Interquartile range (IQR)9

Descriptive statistics

Standard deviation104.04316
Coefficient of variation (CV)2.7200825
Kurtosis8.6229613
Mean38.25
Median Absolute Deviation (MAD)1
Skewness3.1119798
Sum918
Variance10824.978
MonotonicityNot monotonic
2023-12-12T23:59:37.861407image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
1 11
34.4%
2 3
 
9.4%
4 2
 
6.2%
9 2
 
6.2%
28 1
 
3.1%
13 1
 
3.1%
18 1
 
3.1%
368 1
 
3.1%
71 1
 
3.1%
377 1
 
3.1%
(Missing) 8
25.0%
ValueCountFrequency (%)
1 11
34.4%
2 3
 
9.4%
4 2
 
6.2%
9 2
 
6.2%
13 1
 
3.1%
18 1
 
3.1%
28 1
 
3.1%
71 1
 
3.1%
368 1
 
3.1%
377 1
 
3.1%
ValueCountFrequency (%)
377 1
 
3.1%
368 1
 
3.1%
71 1
 
3.1%
28 1
 
3.1%
18 1
 
3.1%
13 1
 
3.1%
9 2
 
6.2%
4 2
 
6.2%
2 3
 
9.4%
1 11
34.4%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)3.1%
Missing0
Missing (%)0.0%
Memory size388.0 B
Minimum2021-09-14 00:00:00
Maximum2021-09-14 00:00:00
2023-12-12T23:59:37.960418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:59:38.063088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-12T23:59:31.904359image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:59:26.293584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:59:26.899838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:59:27.613632image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:59:28.484981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:59:29.303855image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:59:30.181703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:59:31.154036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:59:32.019628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:59:26.367447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:59:26.979945image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:59:27.711734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:59:28.589917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:59:29.413264image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:59:30.312851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:59:31.234998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:59:32.106523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:59:26.431604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:59:27.060603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:59:27.831898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:59:28.716250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:59:29.522527image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:59:30.688988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:59:31.312962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:59:32.214024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:59:26.498949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:59:27.148867image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:59:27.949106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:59:28.823116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:59:29.635096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:59:30.777066image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:59:31.409115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:59:32.338240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:59:26.571586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:59:27.227360image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:59:28.065064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:59:28.930154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:59:29.741413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:59:30.857821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:59:31.532118image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:59:32.431134image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:59:26.639473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:59:27.334193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:59:28.150711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:59:29.026272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:59:29.845036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:59:30.932183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:59:31.625532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:59:32.509202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:59:26.708432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:59:27.412139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:59:28.245586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:59:29.114709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:59:29.943547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:59:30.997674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:59:31.696417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:59:32.605501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:59:26.786915image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:59:27.504013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:59:28.373638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:59:29.206663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:59:30.058981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:59:31.074786image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:59:31.794572image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T23:59:38.158492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
대상자시설종류세부종류유형시설수정원현원종사자수동구시설분포현황서구시설분포현황남구시설분포현황북구시설분포현황광산구시설분포현황
대상자1.0001.0001.0001.0000.8211.0000.9850.7440.8620.6390.0000.6440.573
시설종류1.0001.0001.0001.0000.5891.0001.0000.8200.3860.2940.0000.3780.000
세부종류1.0001.0001.0001.0000.8041.0001.0000.0000.8130.9010.0000.8030.830
유형1.0001.0001.0001.0001.000NaN1.0001.0001.0001.0001.0001.0001.000
시설수0.8210.5890.8041.0001.0001.0000.9820.9331.0001.0001.0001.0001.000
정원1.0001.0001.000NaN1.0001.0001.0001.0001.0001.0001.0001.0001.000
현원0.9851.0001.0001.0000.9821.0001.0000.9220.9790.9790.7030.9810.980
종사자수0.7440.8200.0001.0000.9331.0000.9221.0000.9270.9261.0000.9290.929
동구시설분포현황0.8620.3860.8131.0001.0001.0000.9790.9271.0001.0001.0001.0001.000
서구시설분포현황0.6390.2940.9011.0001.0001.0000.9790.9261.0001.0001.0001.0001.000
남구시설분포현황0.0000.0000.0001.0001.0001.0000.7031.0001.0001.0001.0001.0001.000
북구시설분포현황0.6440.3780.8031.0001.0001.0000.9810.9291.0001.0001.0001.0001.000
광산구시설분포현황0.5730.0000.8301.0001.0001.0000.9800.9291.0001.0001.0001.0001.000
2023-12-12T23:59:38.335486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
대상자시설종류
대상자1.0000.913
시설종류0.9131.000
2023-12-12T23:59:38.466378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시설수정원현원종사자수동구시설분포현황서구시설분포현황북구시설분포현황광산구시설분포현황대상자시설종류
시설수1.0000.9640.4500.9190.8760.9300.9140.9150.4470.238
정원0.9641.0000.9431.0000.9860.9751.0000.9860.7070.707
현원0.4500.9431.0000.6410.2410.0760.3010.1810.7400.784
종사자수0.9191.0000.6411.0000.6450.6770.8060.8150.5800.440
동구시설분포현황0.8760.9860.2410.6451.0000.8400.8220.8300.4640.000
서구시설분포현황0.9300.9750.0760.6770.8401.0000.9220.9340.4630.000
북구시설분포현황0.9141.0000.3010.8060.8220.9221.0000.9490.4580.140
광산구시설분포현황0.9150.9860.1810.8150.8300.9340.9491.0000.4060.000
대상자0.4470.7070.7400.5800.4640.4630.4580.4061.0000.913
시설종류0.2380.7070.7840.4400.0000.0000.1400.0000.9131.000

Missing values

2023-12-12T23:59:32.765106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T23:59:32.987492image/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.
2023-12-12T23:59:33.198799image/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

대상자시설종류형태세부종류유형시설수정원현원종사자수동구시설분포현황서구시설분포현황남구시설분포현황북구시설분포현황광산구시설분포현황데이터기준일자
0노인노인복지시설이용시설재가노인복지시설방문요양98<NA>179917216192817282021-09-14
1노인노인복지시설이용시설재가노인복지시설주야간보호50<NA>674446591310132021-09-14
2노인노인복지시설이용시설재가노인복지시설방문목욕62<NA>2773412151611182021-09-14
3노인노인복지시설이용시설재가노인복지시설재가노인지원9<NA>70857313112021-09-14
4노인노인복지시설이용시설노인여가복지시설노인복지관11<NA><NA>221113422021-09-14
5노인노인복지시설이용시설노인여가복지시설경로당1313<NA><NA><NA>1092302273793682021-09-14
6노인노인복지시설이용시설노인여가복지시설노인교실44<NA><NA>886952042021-09-14
7노인노인복지시설이용시설노인보호전문기관<NA>1<NA><NA>11<NA><NA>1<NA><NA>2021-09-14
8노인노인복지시설이용시설노인일자리지원기관<NA>5<NA><NA>30111112021-09-14
9장애인장애인복지시설이용시설장애인지역사회재활시설장애인복지관7<NA>1866221112212021-09-14
대상자시설종류형태세부종류유형시설수정원현원종사자수동구시설분포현황서구시설분포현황남구시설분포현황북구시설분포현황광산구시설분포현황데이터기준일자
22아동아동복지시설이용시설아동전용시설<NA>1<NA><NA>2<NA><NA><NA><NA>12021-09-14
23아동아동복지시설이용시설지역아동센터<NA>30784167518683214849118712021-09-14
24아동아동복지시설이용시설다함께돌봄센터<NA>5<NA><NA>151<NA>1212021-09-14
25아동아동복지시설이용시설아동보호전문기관<NA>2<NA><NA>31<NA>1<NA>1<NA>2021-09-14
26아동아동복지시설이용시설가정위탁지원센터<NA>1<NA><NA>10<NA><NA><NA>1<NA>2021-09-14
27영유아어린이집이용시설어린이집<NA>107255020367427498572101362923772021-09-14
28기타정신보건센터이용시설정신보건센터기초정신건강복지센터5<NA>151788111112021-09-14
29기타중독관리지원센터이용시설중독관리지원센터중독관리통합지원센터5<NA>136152111112021-09-14
30기타치매통합관리센터이용시설치매통합관리센터치매안심센터5<NA>952794111112021-09-14
31기타다문화가족지원센터이용시설다문화가족지원센터건강가정다문화가족지원센터(여성가족부 소관)5<NA><NA>45111112021-09-14