Overview

Dataset statistics

Number of variables14
Number of observations27
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.3 KiB
Average record size in memory126.9 B

Variable types

Categorical5
Text1
Numeric8

Dataset

Description제주특별자치도 제주시 소재 읍면동별 기초생활 수급자 현황 데이터입니다. 항목 : 일반수급자 가구수,일반수급자 수급권자수,조건부수급자 가구수,조건부수급자 수급권자수,특례수급자 가구수,특례수급자 수급권자수,기타 가구수,기타 수급권자수,시설수급자 가구수,시설수급자 수급권자수
URLhttps://www.data.go.kr/data/15045375/fileData.do

Alerts

시도 has constant value ""Constant
시군구 has constant value ""Constant
기타수급권자수 has constant value ""Constant
데이터기준일자 has constant value ""Constant
일반수급자가구수 is highly overall correlated with 일반수급자수급권자수 and 4 other fieldsHigh correlation
일반수급자수급권자수 is highly overall correlated with 일반수급자가구수 and 4 other fieldsHigh correlation
조건부수급자가구수 is highly overall correlated with 일반수급자가구수 and 4 other fieldsHigh correlation
조건부수급자수급권자수 is highly overall correlated with 일반수급자가구수 and 4 other fieldsHigh correlation
특례수급자가구수 is highly overall correlated with 일반수급자가구수 and 5 other fieldsHigh correlation
특례수급자수급권자수 is highly overall correlated with 일반수급자가구수 and 4 other fieldsHigh correlation
시설수급자가구수 is highly overall correlated with 시설수급자수급권자수High correlation
시설수급자수급권자수 is highly overall correlated with 시설수급자가구수High correlation
기타가구수 is highly overall correlated with 특례수급자가구수High correlation
기타가구수 is highly imbalanced (77.1%)Imbalance
읍면동 has unique valuesUnique
일반수급자가구수 has unique valuesUnique
일반수급자수급권자수 has unique valuesUnique
조건부수급자가구수 has unique valuesUnique
조건부수급자수급권자수 has unique valuesUnique
조건부수급자가구수 has 1 (3.7%) zerosZeros
조건부수급자수급권자수 has 1 (3.7%) zerosZeros
특례수급자가구수 has 3 (11.1%) zerosZeros
특례수급자수급권자수 has 3 (11.1%) zerosZeros
시설수급자가구수 has 5 (18.5%) zerosZeros
시설수급자수급권자수 has 5 (18.5%) zerosZeros

Reproduction

Analysis started2023-12-12 04:15:10.094907
Analysis finished2023-12-12 04:15:17.027859
Duration6.93 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시도
Categorical

CONSTANT 

Distinct1
Distinct (%)3.7%
Missing0
Missing (%)0.0%
Memory size348.0 B
제주특별자치도
27 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
제주특별자치도 27
100.0%

Length

2023-12-12T13:15:17.105060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T13:15:17.186065image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
제주특별자치도 27
100.0%

시군구
Categorical

CONSTANT 

Distinct1
Distinct (%)3.7%
Missing0
Missing (%)0.0%
Memory size348.0 B
제주시
27 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
제주시 27
100.0%

Length

2023-12-12T13:15:17.277026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T13:15:17.383986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
제주시 27
100.0%

읍면동
Text

UNIQUE 

Distinct27
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size348.0 B
2023-12-12T13:15:17.597790image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length3
Mean length3.2592593
Min length2

Characters and Unicode

Total characters88
Distinct characters42
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

Unique27 ?
Unique (%)100.0%

Sample

1st row제주시
2nd row한림읍
3rd row애월읍
4th row구좌읍
5th row조천읍
ValueCountFrequency (%)
제주시 1
 
3.7%
용담1동 1
 
3.7%
이호동 1
 
3.7%
외도동 1
 
3.7%
노형동 1
 
3.7%
연동 1
 
3.7%
오라동 1
 
3.7%
아라동 1
 
3.7%
봉개동 1
 
3.7%
삼양동 1
 
3.7%
Other values (17) 17
63.0%
2023-12-12T13:15:18.001930image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 19
21.6%
도 9
 
10.2%
2 4
 
4.5%
읍 4
 
4.5%
1 4
 
4.5%
삼 3
 
3.4%
이 3
 
3.4%
면 3
 
3.4%
담 2
 
2.3%
일 2
 
2.3%
Other values (32) 35
39.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 80
90.9%
Decimal Number 8
 
9.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 19
23.8%
도 9
 
11.2%
읍 4
 
5.0%
삼 3
 
3.8%
이 3
 
3.8%
면 3
 
3.8%
담 2
 
2.5%
일 2
 
2.5%
라 2
 
2.5%
용 2
 
2.5%
Other values (30) 31
38.8%
Decimal Number
ValueCountFrequency (%)
2 4
50.0%
1 4
50.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 80
90.9%
Common 8
 
9.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 19
23.8%
도 9
 
11.2%
읍 4
 
5.0%
삼 3
 
3.8%
이 3
 
3.8%
면 3
 
3.8%
담 2
 
2.5%
일 2
 
2.5%
라 2
 
2.5%
용 2
 
2.5%
Other values (30) 31
38.8%
Common
ValueCountFrequency (%)
2 4
50.0%
1 4
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 80
90.9%
ASCII 8
 
9.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 19
23.8%
도 9
 
11.2%
읍 4
 
5.0%
삼 3
 
3.8%
이 3
 
3.8%
면 3
 
3.8%
담 2
 
2.5%
일 2
 
2.5%
라 2
 
2.5%
용 2
 
2.5%
Other values (30) 31
38.8%
ASCII
ValueCountFrequency (%)
2 4
50.0%
1 4
50.0%

일반수급자가구수
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct27
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean485.88889
Minimum27
Maximum1125
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size375.0 B
2023-12-12T13:15:18.135997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum27
5-th percentile43.4
Q1249
median438
Q3774
95-th percentile1013.2
Maximum1125
Range1098
Interquartile range (IQR)525

Descriptive statistics

Standard deviation326.11175
Coefficient of variation (CV)0.67116527
Kurtosis-0.90699395
Mean485.88889
Median Absolute Deviation (MAD)210
Skewness0.39410013
Sum13119
Variance106348.87
MonotonicityNot monotonic
2023-12-12T13:15:18.260134image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
27 1
 
3.7%
708 1
 
3.7%
90 1
 
3.7%
102 1
 
3.7%
449 1
 
3.7%
1125 1
 
3.7%
1018 1
 
3.7%
246 1
 
3.7%
877 1
 
3.7%
228 1
 
3.7%
Other values (17) 17
63.0%
ValueCountFrequency (%)
27 1
3.7%
32 1
3.7%
70 1
3.7%
90 1
3.7%
102 1
3.7%
228 1
3.7%
246 1
3.7%
252 1
3.7%
261 1
3.7%
330 1
3.7%
ValueCountFrequency (%)
1125 1
3.7%
1018 1
3.7%
1002 1
3.7%
877 1
3.7%
864 1
3.7%
861 1
3.7%
840 1
3.7%
708 1
3.7%
577 1
3.7%
555 1
3.7%

일반수급자수급권자수
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct27
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean695.51852
Minimum28
Maximum1672
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size375.0 B
2023-12-12T13:15:18.371230image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum28
5-th percentile55
Q1325.5
median549
Q31097.5
95-th percentile1482.1
Maximum1672
Range1644
Interquartile range (IQR)772

Descriptive statistics

Standard deviation489.75601
Coefficient of variation (CV)0.70415956
Kurtosis-0.96745904
Mean695.51852
Median Absolute Deviation (MAD)392
Skewness0.43467072
Sum18779
Variance239860.95
MonotonicityNot monotonic
2023-12-12T13:15:18.508272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
28 1
 
3.7%
948 1
 
3.7%
123 1
 
3.7%
157 1
 
3.7%
746 1
 
3.7%
1672 1
 
3.7%
1438 1
 
3.7%
351 1
 
3.7%
1254 1
 
3.7%
323 1
 
3.7%
Other values (17) 17
63.0%
ValueCountFrequency (%)
28 1
3.7%
43 1
3.7%
83 1
3.7%
123 1
3.7%
157 1
3.7%
291 1
3.7%
323 1
3.7%
328 1
3.7%
351 1
3.7%
418 1
3.7%
ValueCountFrequency (%)
1672 1
3.7%
1501 1
3.7%
1438 1
3.7%
1291 1
3.7%
1266 1
3.7%
1254 1
3.7%
1243 1
3.7%
952 1
3.7%
948 1
3.7%
854 1
3.7%

조건부수급자가구수
Real number (ℝ)

HIGH CORRELATION  UNIQUE  ZEROS 

Distinct27
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean83.185185
Minimum0
Maximum259
Zeros1
Zeros (%)3.7%
Negative0
Negative (%)0.0%
Memory size375.0 B
2023-12-12T13:15:18.641818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1.3
Q134
median74
Q3125
95-th percentile232.9
Maximum259
Range259
Interquartile range (IQR)91

Descriptive statistics

Standard deviation69.757292
Coefficient of variation (CV)0.83857831
Kurtosis0.9589831
Mean83.185185
Median Absolute Deviation (MAD)47
Skewness1.1502019
Sum2246
Variance4866.0798
MonotonicityNot monotonic
2023-12-12T13:15:18.755356image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
0 1
 
3.7%
127 1
 
3.7%
18 1
 
3.7%
14 1
 
3.7%
69 1
 
3.7%
238 1
 
3.7%
259 1
 
3.7%
39 1
 
3.7%
131 1
 
3.7%
27 1
 
3.7%
Other values (17) 17
63.0%
ValueCountFrequency (%)
0 1
3.7%
1 1
3.7%
2 1
3.7%
14 1
3.7%
18 1
3.7%
27 1
3.7%
30 1
3.7%
38 1
3.7%
39 1
3.7%
49 1
3.7%
ValueCountFrequency (%)
259 1
3.7%
238 1
3.7%
221 1
3.7%
136 1
3.7%
131 1
3.7%
128 1
3.7%
127 1
3.7%
123 1
3.7%
85 1
3.7%
83 1
3.7%

조건부수급자수급권자수
Real number (ℝ)

HIGH CORRELATION  UNIQUE  ZEROS 

Distinct27
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean162.77778
Minimum0
Maximum508
Zeros1
Zeros (%)3.7%
Negative0
Negative (%)0.0%
Memory size375.0 B
2023-12-12T13:15:19.112979image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1.6
Q157.5
median136
Q3265
95-th percentile436.5
Maximum508
Range508
Interquartile range (IQR)207.5

Descriptive statistics

Standard deviation139.75537
Coefficient of variation (CV)0.85856543
Kurtosis0.32151703
Mean162.77778
Median Absolute Deviation (MAD)85
Skewness0.9972836
Sum4395
Variance19531.564
MonotonicityNot monotonic
2023-12-12T13:15:19.230586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
0 1
 
3.7%
251 1
 
3.7%
34 1
 
3.7%
26 1
 
3.7%
154 1
 
3.7%
508 1
 
3.7%
441 1
 
3.7%
88 1
 
3.7%
279 1
 
3.7%
57 1
 
3.7%
Other values (17) 17
63.0%
ValueCountFrequency (%)
0 1
3.7%
1 1
3.7%
3 1
3.7%
26 1
3.7%
34 1
3.7%
51 1
3.7%
57 1
3.7%
58 1
3.7%
60 1
3.7%
88 1
3.7%
ValueCountFrequency (%)
508 1
3.7%
441 1
3.7%
426 1
3.7%
290 1
3.7%
283 1
3.7%
280 1
3.7%
279 1
3.7%
251 1
3.7%
199 1
3.7%
160 1
3.7%

특례수급자가구수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct12
Distinct (%)44.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.5925926
Minimum0
Maximum25
Zeros3
Zeros (%)11.1%
Negative0
Negative (%)0.0%
Memory size375.0 B
2023-12-12T13:15:19.333957image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median3
Q36.5
95-th percentile15.7
Maximum25
Range25
Interquartile range (IQR)5.5

Descriptive statistics

Standard deviation6.2033444
Coefficient of variation (CV)1.1092073
Kurtosis2.3554494
Mean5.5925926
Median Absolute Deviation (MAD)2
Skewness1.5799501
Sum151
Variance38.481481
MonotonicityNot monotonic
2023-12-12T13:15:19.430336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
1 6
22.2%
3 4
14.8%
0 3
11.1%
6 3
11.1%
5 2
 
7.4%
2 2
 
7.4%
13 2
 
7.4%
25 1
 
3.7%
15 1
 
3.7%
7 1
 
3.7%
Other values (2) 2
 
7.4%
ValueCountFrequency (%)
0 3
11.1%
1 6
22.2%
2 2
 
7.4%
3 4
14.8%
5 2
 
7.4%
6 3
11.1%
7 1
 
3.7%
12 1
 
3.7%
13 2
 
7.4%
15 1
 
3.7%
ValueCountFrequency (%)
25 1
 
3.7%
16 1
 
3.7%
15 1
 
3.7%
13 2
7.4%
12 1
 
3.7%
7 1
 
3.7%
6 3
11.1%
5 2
7.4%
3 4
14.8%
2 2
7.4%

특례수급자수급권자수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct13
Distinct (%)48.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.3703704
Minimum0
Maximum31
Zeros3
Zeros (%)11.1%
Negative0
Negative (%)0.0%
Memory size375.0 B
2023-12-12T13:15:19.527426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median3
Q38
95-th percentile17.8
Maximum31
Range31
Interquartile range (IQR)7

Descriptive statistics

Standard deviation7.2331935
Coefficient of variation (CV)1.1354432
Kurtosis4.0177619
Mean6.3703704
Median Absolute Deviation (MAD)2
Skewness1.8601921
Sum172
Variance52.319088
MonotonicityNot monotonic
2023-12-12T13:15:19.625886image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
3 5
18.5%
1 5
18.5%
0 3
11.1%
8 3
11.1%
5 2
 
7.4%
14 2
 
7.4%
6 1
 
3.7%
31 1
 
3.7%
2 1
 
3.7%
15 1
 
3.7%
Other values (3) 3
11.1%
ValueCountFrequency (%)
0 3
11.1%
1 5
18.5%
2 1
 
3.7%
3 5
18.5%
4 1
 
3.7%
5 2
 
7.4%
6 1
 
3.7%
8 3
11.1%
13 1
 
3.7%
14 2
 
7.4%
ValueCountFrequency (%)
31 1
 
3.7%
19 1
 
3.7%
15 1
 
3.7%
14 2
 
7.4%
13 1
 
3.7%
8 3
11.1%
6 1
 
3.7%
5 2
 
7.4%
4 1
 
3.7%
3 5
18.5%

기타가구수
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)7.4%
Missing0
Missing (%)0.0%
Memory size348.0 B
0
26 
2
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)3.7%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26
96.3%
2 1
 
3.7%

Length

2023-12-12T13:15:19.727363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T13:15:19.799118image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 26
96.3%
2 1
 
3.7%

기타수급권자수
Categorical

CONSTANT 

Distinct1
Distinct (%)3.7%
Missing0
Missing (%)0.0%
Memory size348.0 B
0
27 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 27
100.0%

Length

2023-12-12T13:15:19.877606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T13:15:19.957408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 27
100.0%

시설수급자가구수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct10
Distinct (%)37.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean48.444444
Minimum0
Maximum1170
Zeros5
Zeros (%)18.5%
Negative0
Negative (%)0.0%
Memory size375.0 B
2023-12-12T13:15:20.030242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median3
Q34.5
95-th percentile36
Maximum1170
Range1170
Interquartile range (IQR)3.5

Descriptive statistics

Standard deviation224.33497
Coefficient of variation (CV)4.6307678
Kurtosis26.897619
Mean48.444444
Median Absolute Deviation (MAD)2
Skewness5.1821279
Sum1308
Variance50326.179
MonotonicityNot monotonic
2023-12-12T13:15:20.125197image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
0 5
18.5%
4 4
14.8%
2 4
14.8%
1 4
14.8%
3 3
11.1%
36 2
 
7.4%
5 2
 
7.4%
1170 1
 
3.7%
7 1
 
3.7%
12 1
 
3.7%
ValueCountFrequency (%)
0 5
18.5%
1 4
14.8%
2 4
14.8%
3 3
11.1%
4 4
14.8%
5 2
 
7.4%
7 1
 
3.7%
12 1
 
3.7%
36 2
 
7.4%
1170 1
 
3.7%
ValueCountFrequency (%)
1170 1
 
3.7%
36 2
 
7.4%
12 1
 
3.7%
7 1
 
3.7%
5 2
 
7.4%
4 4
14.8%
3 3
11.1%
2 4
14.8%
1 4
14.8%
0 5
18.5%

시설수급자수급권자수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct10
Distinct (%)37.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean48.444444
Minimum0
Maximum1170
Zeros5
Zeros (%)18.5%
Negative0
Negative (%)0.0%
Memory size375.0 B
2023-12-12T13:15:20.217048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median3
Q34.5
95-th percentile36
Maximum1170
Range1170
Interquartile range (IQR)3.5

Descriptive statistics

Standard deviation224.33497
Coefficient of variation (CV)4.6307678
Kurtosis26.897619
Mean48.444444
Median Absolute Deviation (MAD)2
Skewness5.1821279
Sum1308
Variance50326.179
MonotonicityNot monotonic
2023-12-12T13:15:20.315181image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
0 5
18.5%
4 4
14.8%
2 4
14.8%
1 4
14.8%
3 3
11.1%
36 2
 
7.4%
5 2
 
7.4%
1170 1
 
3.7%
7 1
 
3.7%
12 1
 
3.7%
ValueCountFrequency (%)
0 5
18.5%
1 4
14.8%
2 4
14.8%
3 3
11.1%
4 4
14.8%
5 2
 
7.4%
7 1
 
3.7%
12 1
 
3.7%
36 2
 
7.4%
1170 1
 
3.7%
ValueCountFrequency (%)
1170 1
 
3.7%
36 2
 
7.4%
12 1
 
3.7%
7 1
 
3.7%
5 2
 
7.4%
4 4
14.8%
3 3
11.1%
2 4
14.8%
1 4
14.8%
0 5
18.5%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)3.7%
Missing0
Missing (%)0.0%
Memory size348.0 B
2023-06-30
27 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-06-30
2nd row2023-06-30
3rd row2023-06-30
4th row2023-06-30
5th row2023-06-30

Common Values

ValueCountFrequency (%)
2023-06-30 27
100.0%

Length

2023-12-12T13:15:20.432411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T13:15:20.518348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-06-30 27
100.0%

Interactions

2023-12-12T13:15:15.900986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:15:10.408056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:15:11.065416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:15:11.839807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:15:12.874770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:15:13.598556image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:15:14.296135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:15:15.105059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:15:15.986423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:15:10.493933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:15:11.145577image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:15:11.939095image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:15:12.950274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:15:13.683869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:15:14.388393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:15:15.214554image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:15:16.088782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:15:10.580720image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:15:11.231774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:15:12.031356image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:15:13.033833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:15:13.769034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:15:14.487371image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:15:15.311886image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:15:16.185463image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:15:10.658290image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:15:11.311875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:15:12.131746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:15:13.105801image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:15:13.853717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:15:14.578764image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:15:15.407162image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:15:16.267166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:15:10.731017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:15:11.444382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:15:12.212679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:15:13.218386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:15:13.938913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:15:14.677517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:15:15.521378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:15:16.356057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:15:10.813938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:15:11.534013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:15:12.297589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:15:13.316902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:15:14.014932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:15:14.793308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:15:15.621695image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:15:16.449676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:15:10.902718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:15:11.623476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:15:12.398911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:15:13.405826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:15:14.093911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:15:14.900889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:15:15.713306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:15:16.565531image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:15:10.976870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:15:11.723901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:15:12.782609image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:15:13.500021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:15:14.185038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:15:15.000267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:15:15.813057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T13:15:20.576203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
읍면동일반수급자가구수일반수급자수급권자수조건부수급자가구수조건부수급자수급권자수특례수급자가구수특례수급자수급권자수기타가구수시설수급자가구수시설수급자수급권자수
읍면동1.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
일반수급자가구수1.0001.0000.8960.9580.9290.7590.8060.0000.0000.000
일반수급자수급권자수1.0000.8961.0000.8690.9300.5420.7900.0000.0000.000
조건부수급자가구수1.0000.9580.8691.0000.9700.7250.6860.7150.0000.000
조건부수급자수급권자수1.0000.9290.9300.9701.0000.6230.8070.0000.0000.000
특례수급자가구수1.0000.7590.5420.7250.6231.0000.8701.0000.0000.000
특례수급자수급권자수1.0000.8060.7900.6860.8070.8701.0000.2920.0000.000
기타가구수1.0000.0000.0000.7150.0001.0000.2921.0000.0000.000
시설수급자가구수1.0000.0000.0000.0000.0000.0000.0000.0001.0000.648
시설수급자수급권자수1.0000.0000.0000.0000.0000.0000.0000.0000.6481.000
2023-12-12T13:15:20.690920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
일반수급자가구수일반수급자수급권자수조건부수급자가구수조건부수급자수급권자수특례수급자가구수특례수급자수급권자수시설수급자가구수시설수급자수급권자수기타가구수
일반수급자가구수1.0000.9900.9820.9770.6770.6500.3000.3000.000
일반수급자수급권자수0.9901.0000.9670.9790.7300.7010.3110.3110.000
조건부수급자가구수0.9820.9671.0000.9830.6630.6400.2030.2030.469
조건부수급자수급권자수0.9770.9790.9831.0000.7000.6750.2460.2460.000
특례수급자가구수0.6770.7300.6630.7001.0000.9910.1700.1700.894
특례수급자수급권자수0.6500.7010.6400.6750.9911.0000.1540.1540.173
시설수급자가구수0.3000.3110.2030.2460.1700.1541.0001.0000.000
시설수급자수급권자수0.3000.3110.2030.2460.1700.1541.0001.0000.000
기타가구수0.0000.0000.4690.0000.8940.1730.0000.0001.000

Missing values

2023-12-12T13:15:16.714671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T13:15:16.933729image/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

시도시군구읍면동일반수급자가구수일반수급자수급권자수조건부수급자가구수조건부수급자수급권자수특례수급자가구수특례수급자수급권자수기타가구수기타수급권자수시설수급자가구수시설수급자수급권자수데이터기준일자
0제주특별자치도제주시제주시2728000000117011702023-06-30
1제주특별자치도제주시한림읍7089481272515500442023-06-30
2제주특별자치도제주시애월읍8641266123280660036362023-06-30
3제주특별자치도제주시구좌읍406549541026800222023-06-30
4제주특별자치도제주시조천읍57795285199253100552023-06-30
5제주특별자치도제주시한경면26132830511200442023-06-30
6제주특별자치도제주시추자면7083230000002023-06-30
7제주특별자치도제주시우도면3243112300002023-06-30
8제주특별자치도제주시일도1동25229149581100002023-06-30
9제주특별자치도제주시일도2동8401243136290151500112023-06-30
시도시군구읍면동일반수급자가구수일반수급자수급권자수조건부수급자가구수조건부수급자수급권자수특례수급자가구수특례수급자수급권자수기타가구수기타수급권자수시설수급자가구수시설수급자수급권자수데이터기준일자
17제주특별자치도제주시화북동8611291128283131300442023-06-30
18제주특별자치도제주시삼양동555854811467800222023-06-30
19제주특별자치도제주시봉개동22832327573300332023-06-30
20제주특별자치도제주시아라동877125413127912142036362023-06-30
21제주특별자치도제주시오라동24635139883400112023-06-30
22제주특별자치도제주시연동101814382594411100552023-06-30
23제주특별자치도제주시노형동11251672238508161900112023-06-30
24제주특별자치도제주시외도동44974669154550012122023-06-30
25제주특별자치도제주시이호동10215714260000332023-06-30
26제주특별자치도제주시도두동9012318341100002023-06-30