Overview

Dataset statistics

Number of variables14
Number of observations50
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory6.2 KiB
Average record size in memory126.6 B

Variable types

Categorical1
Text1
Numeric12

Dataset

Description특성별로 만족도(매우만족, 약간만족, 보통, 약간 불만족, 매우 불만족), 불만족 이유(경제적 부담, 시간부족, 체력/건강 문제, 취미가 없음, 여가시설만족도, 여가정보/프로그램 부족, 교통 혼잡/불편, 함께할 사람이 부재)등의 정보이다.
Author인천광역시
URLhttps://data.incheon.go.kr/findData/publicDataDetail?dataId=15066207&srcSe=7661IVAWM27C61E190

Alerts

문화여가시설(접근성과 충분 정도) 매우 불만족 (퍼센트) is highly overall correlated with 전반적인 여가활동 매우 불만족 (퍼센트)High correlation
문화여가시설(접근성과 충분 정도) 약간 불만족 (퍼센트) is highly overall correlated with 문화여가시설(접근성과 충분 정도) 보통 (퍼센트) and 7 other fieldsHigh correlation
문화여가시설(접근성과 충분 정도) 보통 (퍼센트) is highly overall correlated with 문화여가시설(접근성과 충분 정도) 약간 불만족 (퍼센트) and 2 other fieldsHigh correlation
문화여가시설(접근성과 충분 정도) 약간 만족 (퍼센트) is highly overall correlated with 문화여가시설(접근성과 충분 정도) 약간 불만족 (퍼센트) and 6 other fieldsHigh correlation
문화여가시설(접근성과 충분 정도) 매우 만족 (퍼센트) is highly overall correlated with 문화여가시설(접근성과 충분 정도) 약간 불만족 (퍼센트) and 4 other fieldsHigh correlation
문화여가시설(접근성과 충분 정도) 5점 평균 (점) is highly overall correlated with 문화여가시설(접근성과 충분 정도) 약간 불만족 (퍼센트) and 6 other fieldsHigh correlation
전반적인 여가활동 매우 불만족 (퍼센트) is highly overall correlated with 문화여가시설(접근성과 충분 정도) 매우 불만족 (퍼센트)High correlation
전반적인 여가활동 약간 불만족 (퍼센트) is highly overall correlated with 문화여가시설(접근성과 충분 정도) 약간 불만족 (퍼센트) and 6 other fieldsHigh correlation
전반적인 여가활동 보통 (퍼센트) is highly overall correlated with 문화여가시설(접근성과 충분 정도) 보통 (퍼센트) and 1 other fieldsHigh correlation
전반적인 여가활동 약간 만족 (퍼센트) is highly overall correlated with 문화여가시설(접근성과 충분 정도) 약간 불만족 (퍼센트) and 5 other fieldsHigh correlation
전반적인 여가활동 매우 만족 (퍼센트) is highly overall correlated with 문화여가시설(접근성과 충분 정도) 약간 불만족 (퍼센트) and 5 other fieldsHigh correlation
전반적인 여가활동 5점 평균 (점) is highly overall correlated with 문화여가시설(접근성과 충분 정도) 약간 불만족 (퍼센트) and 6 other fieldsHigh correlation
특성별(2) has unique valuesUnique

Reproduction

Analysis started2024-03-18 02:27:36.406228
Analysis finished2024-03-18 02:27:49.655119
Duration13.25 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

특성별(1)
Categorical

Distinct9
Distinct (%)18.0%
Missing0
Missing (%)0.0%
Memory size532.0 B
군구별
10 
직업별
월평균소득별
연령별
가구원수별
Other values (4)
13 

Length

Max length7
Median length3
Mean length4.04
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
군구별 10
20.0%
직업별 8
16.0%
월평균소득별 8
16.0%
연령별 6
12.0%
가구원수별 5
10.0%
학력별 4
 
8.0%
주거형태별 4
 
8.0%
주거점유형태별 3
 
6.0%
성별 2
 
4.0%

Length

2024-03-18T11:27:49.717295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-18T11:27:49.856680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
군구별 10
20.0%
직업별 8
16.0%
월평균소득별 8
16.0%
연령별 6
12.0%
가구원수별 5
10.0%
학력별 4
 
8.0%
주거형태별 4
 
8.0%
주거점유형태별 3
 
6.0%
성별 2
 
4.0%

특성별(2)
Text

UNIQUE 

Distinct50
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size532.0 B
2024-03-18T11:27:50.055251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length7.5
Mean length4.92
Min length2

Characters and Unicode

Total characters246
Distinct characters76
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique50 ?
Unique (%)100.0%

Sample

1st row중구
2nd row동구
3rd row미추홀구
4th row연수구
5th row남동구
ValueCountFrequency (%)
미만 7
 
9.7%
5
 
6.9%
이상 3
 
4.2%
기타 2
 
2.8%
중구 1
 
1.4%
기능노무 1
 
1.4%
4인 1
 
1.4%
학생 1
 
1.4%
주부 1
 
1.4%
무직/기타 1
 
1.4%
Other values (49) 49
68.1%
2024-03-18T11:27:50.332423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 33
 
13.4%
22
 
8.9%
15
 
6.1%
~ 11
 
4.5%
9
 
3.7%
8
 
3.3%
8
 
3.3%
8
 
3.3%
3 6
 
2.4%
5
 
2.0%
Other values (66) 121
49.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 142
57.7%
Decimal Number 69
28.0%
Space Separator 22
 
8.9%
Math Symbol 11
 
4.5%
Other Punctuation 2
 
0.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
15
 
10.6%
9
 
6.3%
8
 
5.6%
8
 
5.6%
8
 
5.6%
5
 
3.5%
5
 
3.5%
4
 
2.8%
4
 
2.8%
4
 
2.8%
Other values (54) 72
50.7%
Decimal Number
ValueCountFrequency (%)
0 33
47.8%
3 6
 
8.7%
9 5
 
7.2%
5 5
 
7.2%
4 5
 
7.2%
2 5
 
7.2%
1 5
 
7.2%
6 3
 
4.3%
7 2
 
2.9%
Space Separator
ValueCountFrequency (%)
22
100.0%
Math Symbol
ValueCountFrequency (%)
~ 11
100.0%
Other Punctuation
ValueCountFrequency (%)
/ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 142
57.7%
Common 104
42.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
15
 
10.6%
9
 
6.3%
8
 
5.6%
8
 
5.6%
8
 
5.6%
5
 
3.5%
5
 
3.5%
4
 
2.8%
4
 
2.8%
4
 
2.8%
Other values (54) 72
50.7%
Common
ValueCountFrequency (%)
0 33
31.7%
22
21.2%
~ 11
 
10.6%
3 6
 
5.8%
9 5
 
4.8%
5 5
 
4.8%
4 5
 
4.8%
2 5
 
4.8%
1 5
 
4.8%
6 3
 
2.9%
Other values (2) 4
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 142
57.7%
ASCII 104
42.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 33
31.7%
22
21.2%
~ 11
 
10.6%
3 6
 
5.8%
9 5
 
4.8%
5 5
 
4.8%
4 5
 
4.8%
2 5
 
4.8%
1 5
 
4.8%
6 3
 
2.9%
Other values (2) 4
 
3.8%
Hangul
ValueCountFrequency (%)
15
 
10.6%
9
 
6.3%
8
 
5.6%
8
 
5.6%
8
 
5.6%
5
 
3.5%
5
 
3.5%
4
 
2.8%
4
 
2.8%
4
 
2.8%
Other values (54) 72
50.7%
Distinct33
Distinct (%)66.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.256
Minimum1.2
Maximum24.1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size582.0 B
2024-03-18T11:27:50.464129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.2
5-th percentile3.305
Q14.8
median5.35
Q36.075
95-th percentile14.215
Maximum24.1
Range22.9
Interquartile range (IQR)1.275

Descriptive statistics

Standard deviation3.8371524
Coefficient of variation (CV)0.61335557
Kurtosis11.752196
Mean6.256
Median Absolute Deviation (MAD)0.65
Skewness3.2621074
Sum312.8
Variance14.723739
MonotonicityNot monotonic
2024-03-18T11:27:50.693561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=33)
ValueCountFrequency (%)
5.1 5
 
10.0%
5.4 3
 
6.0%
4.4 3
 
6.0%
5.3 2
 
4.0%
4.8 2
 
4.0%
5.0 2
 
4.0%
5.9 2
 
4.0%
6.8 2
 
4.0%
5.7 2
 
4.0%
2.9 2
 
4.0%
Other values (23) 25
50.0%
ValueCountFrequency (%)
1.2 1
 
2.0%
2.9 2
4.0%
3.8 1
 
2.0%
4.1 1
 
2.0%
4.2 1
 
2.0%
4.4 3
6.0%
4.5 1
 
2.0%
4.6 1
 
2.0%
4.7 1
 
2.0%
4.8 2
4.0%
ValueCountFrequency (%)
24.1 1
2.0%
18.4 1
2.0%
17.5 1
2.0%
10.2 1
2.0%
8.1 1
2.0%
7.8 1
2.0%
7.4 1
2.0%
6.9 1
2.0%
6.8 2
4.0%
6.5 2
4.0%
Distinct39
Distinct (%)78.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean33.01
Minimum24.7
Maximum47.4
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size582.0 B
2024-03-18T11:27:50.859863image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum24.7
5-th percentile27.27
Q130.7
median32.45
Q334.875
95-th percentile39.82
Maximum47.4
Range22.7
Interquartile range (IQR)4.175

Descriptive statistics

Standard deviation4.3679374
Coefficient of variation (CV)0.13232164
Kurtosis2.6999633
Mean33.01
Median Absolute Deviation (MAD)2.15
Skewness1.1291001
Sum1650.5
Variance19.078878
MonotonicityNot monotonic
2024-03-18T11:27:50.999747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=39)
ValueCountFrequency (%)
32.7 3
 
6.0%
31.8 3
 
6.0%
30.2 2
 
4.0%
31.2 2
 
4.0%
30.7 2
 
4.0%
35.3 2
 
4.0%
27.6 2
 
4.0%
31.3 2
 
4.0%
32.3 2
 
4.0%
34.2 1
 
2.0%
Other values (29) 29
58.0%
ValueCountFrequency (%)
24.7 1
2.0%
25.3 1
2.0%
27.0 1
2.0%
27.6 2
4.0%
28.4 1
2.0%
28.8 1
2.0%
29.1 1
2.0%
29.7 1
2.0%
29.9 1
2.0%
30.2 2
4.0%
ValueCountFrequency (%)
47.4 1
2.0%
46.3 1
2.0%
40.0 1
2.0%
39.6 1
2.0%
38.6 1
2.0%
37.3 1
2.0%
37.0 1
2.0%
36.2 1
2.0%
36.0 1
2.0%
35.5 1
2.0%
Distinct38
Distinct (%)76.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean47.566
Minimum30.7
Maximum56.5
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size582.0 B
2024-03-18T11:27:51.112476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum30.7
5-th percentile40.82
Q146.65
median48
Q349.975
95-th percentile53.575
Maximum56.5
Range25.8
Interquartile range (IQR)3.325

Descriptive statistics

Standard deviation4.5444117
Coefficient of variation (CV)0.095539076
Kurtosis3.9232693
Mean47.566
Median Absolute Deviation (MAD)1.4
Skewness-1.3279407
Sum2378.3
Variance20.651678
MonotonicityNot monotonic
2024-03-18T11:27:51.237410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=38)
ValueCountFrequency (%)
48.0 3
 
6.0%
50.6 3
 
6.0%
48.2 3
 
6.0%
48.5 2
 
4.0%
47.1 2
 
4.0%
53.3 2
 
4.0%
48.3 2
 
4.0%
47.3 2
 
4.0%
46.6 2
 
4.0%
44.7 1
 
2.0%
Other values (28) 28
56.0%
ValueCountFrequency (%)
30.7 1
2.0%
34.6 1
2.0%
40.1 1
2.0%
41.7 1
2.0%
41.9 1
2.0%
42.1 1
2.0%
43.1 1
2.0%
44.6 1
2.0%
44.7 1
2.0%
45.5 1
2.0%
ValueCountFrequency (%)
56.5 1
 
2.0%
55.5 1
 
2.0%
53.8 1
 
2.0%
53.3 2
4.0%
52.5 1
 
2.0%
52.1 1
 
2.0%
51.3 1
 
2.0%
50.6 3
6.0%
50.4 1
 
2.0%
50.2 1
 
2.0%
Distinct40
Distinct (%)80.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11.634
Minimum4.6
Maximum23.2
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size582.0 B
2024-03-18T11:27:51.352116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4.6
5-th percentile6.925
Q19.45
median11.7
Q313.4
95-th percentile16.97
Maximum23.2
Range18.6
Interquartile range (IQR)3.95

Descriptive statistics

Standard deviation3.499015
Coefficient of variation (CV)0.30075769
Kurtosis1.6664153
Mean11.634
Median Absolute Deviation (MAD)1.9
Skewness0.78218276
Sum581.7
Variance12.243106
MonotonicityNot monotonic
2024-03-18T11:27:51.468095image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=40)
ValueCountFrequency (%)
7.6 3
 
6.0%
9.9 3
 
6.0%
12.3 3
 
6.0%
13.2 2
 
4.0%
12.0 2
 
4.0%
13.4 2
 
4.0%
11.2 2
 
4.0%
4.6 1
 
2.0%
10.0 1
 
2.0%
13.5 1
 
2.0%
Other values (30) 30
60.0%
ValueCountFrequency (%)
4.6 1
 
2.0%
6.6 1
 
2.0%
6.7 1
 
2.0%
7.2 1
 
2.0%
7.3 1
 
2.0%
7.5 1
 
2.0%
7.6 3
6.0%
8.3 1
 
2.0%
8.7 1
 
2.0%
9.3 1
 
2.0%
ValueCountFrequency (%)
23.2 1
2.0%
20.2 1
2.0%
17.6 1
2.0%
16.2 1
2.0%
15.9 1
2.0%
15.0 1
2.0%
14.9 1
2.0%
14.4 1
2.0%
14.3 1
2.0%
14.0 1
2.0%
Distinct23
Distinct (%)46.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.552
Minimum0.2
Maximum4.5
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size582.0 B
2024-03-18T11:27:51.579969image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.2
5-th percentile0.445
Q11.125
median1.45
Q31.875
95-th percentile2.51
Maximum4.5
Range4.3
Interquartile range (IQR)0.75

Descriptive statistics

Standard deviation0.72681581
Coefficient of variation (CV)0.46830916
Kurtosis4.7057553
Mean1.552
Median Absolute Deviation (MAD)0.35
Skewness1.3411781
Sum77.6
Variance0.52826122
MonotonicityNot monotonic
2024-03-18T11:27:51.672798image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
1.4 7
14.0%
1.8 5
 
10.0%
1.1 4
 
8.0%
1.5 4
 
8.0%
1.3 3
 
6.0%
1.7 2
 
4.0%
1.2 2
 
4.0%
2.1 2
 
4.0%
2.0 2
 
4.0%
2.2 2
 
4.0%
Other values (13) 17
34.0%
ValueCountFrequency (%)
0.2 1
 
2.0%
0.4 2
 
4.0%
0.5 1
 
2.0%
0.6 1
 
2.0%
0.8 2
 
4.0%
1.0 2
 
4.0%
1.1 4
8.0%
1.2 2
 
4.0%
1.3 3
6.0%
1.4 7
14.0%
ValueCountFrequency (%)
4.5 1
 
2.0%
3.2 1
 
2.0%
2.6 1
 
2.0%
2.4 1
 
2.0%
2.3 1
 
2.0%
2.2 2
 
4.0%
2.1 2
 
4.0%
2.0 2
 
4.0%
1.9 2
 
4.0%
1.8 5
10.0%
Distinct27
Distinct (%)54.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.6918
Minimum2.23
Maximum2.92
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size582.0 B
2024-03-18T11:27:51.769479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.23
5-th percentile2.4605
Q12.66
median2.72
Q32.75
95-th percentile2.852
Maximum2.92
Range0.69
Interquartile range (IQR)0.09

Descriptive statistics

Standard deviation0.12402584
Coefficient of variation (CV)0.046075428
Kurtosis4.2521021
Mean2.6918
Median Absolute Deviation (MAD)0.05
Skewness-1.6388619
Sum134.59
Variance0.015382408
MonotonicityNot monotonic
2024-03-18T11:27:51.879016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
2.72 6
 
12.0%
2.74 5
 
10.0%
2.65 3
 
6.0%
2.66 3
 
6.0%
2.7 3
 
6.0%
2.77 2
 
4.0%
2.69 2
 
4.0%
2.62 2
 
4.0%
2.75 2
 
4.0%
2.78 2
 
4.0%
Other values (17) 20
40.0%
ValueCountFrequency (%)
2.23 1
 
2.0%
2.33 1
 
2.0%
2.42 1
 
2.0%
2.51 1
 
2.0%
2.52 1
 
2.0%
2.57 1
 
2.0%
2.59 1
 
2.0%
2.62 2
4.0%
2.65 3
6.0%
2.66 3
6.0%
ValueCountFrequency (%)
2.92 1
2.0%
2.88 1
2.0%
2.87 1
2.0%
2.83 1
2.0%
2.8 1
2.0%
2.79 2
4.0%
2.78 2
4.0%
2.77 2
4.0%
2.76 1
2.0%
2.75 2
4.0%

전반적인 여가활동 매우 불만족 (퍼센트)
Real number (ℝ)

HIGH CORRELATION 

Distinct33
Distinct (%)66.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.8
Minimum1.2
Maximum22.5
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size582.0 B
2024-03-18T11:27:52.030817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.2
5-th percentile2.98
Q14.525
median5.15
Q35.675
95-th percentile11
Maximum22.5
Range21.3
Interquartile range (IQR)1.15

Descriptive statistics

Standard deviation3.4905119
Coefficient of variation (CV)0.6018124
Kurtosis13.719208
Mean5.8
Median Absolute Deviation (MAD)0.6
Skewness3.4574884
Sum290
Variance12.183673
MonotonicityNot monotonic
2024-03-18T11:27:52.162889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=33)
ValueCountFrequency (%)
5.2 6
 
12.0%
4.9 4
 
8.0%
4.5 3
 
6.0%
4.0 2
 
4.0%
6.0 2
 
4.0%
4.8 2
 
4.0%
5.0 2
 
4.0%
5.3 2
 
4.0%
5.6 2
 
4.0%
4.6 2
 
4.0%
Other values (23) 23
46.0%
ValueCountFrequency (%)
1.2 1
 
2.0%
2.4 1
 
2.0%
2.8 1
 
2.0%
3.2 1
 
2.0%
3.4 1
 
2.0%
3.8 1
 
2.0%
4.0 2
4.0%
4.1 1
 
2.0%
4.4 1
 
2.0%
4.5 3
6.0%
ValueCountFrequency (%)
22.5 1
2.0%
18.8 1
2.0%
11.9 1
2.0%
9.9 1
2.0%
7.3 1
2.0%
7.2 1
2.0%
6.8 1
2.0%
6.7 1
2.0%
6.2 1
2.0%
6.1 1
2.0%

전반적인 여가활동 약간 불만족 (퍼센트)
Real number (ℝ)

HIGH CORRELATION 

Distinct41
Distinct (%)82.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean31.528
Minimum23.5
Maximum46.2
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size582.0 B
2024-03-18T11:27:52.283676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum23.5
5-th percentile25.38
Q129.1
median31.85
Q333.6
95-th percentile37.085
Maximum46.2
Range22.7
Interquartile range (IQR)4.5

Descriptive statistics

Standard deviation4.0340915
Coefficient of variation (CV)0.12795266
Kurtosis2.6609098
Mean31.528
Median Absolute Deviation (MAD)2.3
Skewness0.73269289
Sum1576.4
Variance16.273894
MonotonicityNot monotonic
2024-03-18T11:27:52.394350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=41)
ValueCountFrequency (%)
33.5 3
 
6.0%
32.3 3
 
6.0%
27.7 2
 
4.0%
25.6 2
 
4.0%
31.3 2
 
4.0%
34.2 2
 
4.0%
33.6 2
 
4.0%
32.0 1
 
2.0%
38.3 1
 
2.0%
27.3 1
 
2.0%
Other values (31) 31
62.0%
ValueCountFrequency (%)
23.5 1
2.0%
23.7 1
2.0%
25.2 1
2.0%
25.6 2
4.0%
27.3 1
2.0%
27.4 1
2.0%
27.7 2
4.0%
28.1 1
2.0%
28.4 1
2.0%
28.5 1
2.0%
ValueCountFrequency (%)
46.2 1
2.0%
39.6 1
2.0%
38.3 1
2.0%
35.6 1
2.0%
35.1 1
2.0%
34.9 1
2.0%
34.8 1
2.0%
34.7 1
2.0%
34.4 1
2.0%
34.2 2
4.0%

전반적인 여가활동 보통 (퍼센트)
Real number (ℝ)

HIGH CORRELATION 

Distinct41
Distinct (%)82.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean49.932
Minimum33.1
Maximum59.5
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size582.0 B
2024-03-18T11:27:52.506768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum33.1
5-th percentile42.69
Q149.15
median50.15
Q352.225
95-th percentile55.375
Maximum59.5
Range26.4
Interquartile range (IQR)3.075

Descriptive statistics

Standard deviation4.2516955
Coefficient of variation (CV)0.085149713
Kurtosis4.5067754
Mean49.932
Median Absolute Deviation (MAD)1.75
Skewness-1.3201919
Sum2496.6
Variance18.076914
MonotonicityNot monotonic
2024-03-18T11:27:52.632631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=41)
ValueCountFrequency (%)
50.3 3
 
6.0%
50.0 3
 
6.0%
52.9 2
 
4.0%
50.1 2
 
4.0%
49.7 2
 
4.0%
52.7 2
 
4.0%
46.1 2
 
4.0%
48.7 1
 
2.0%
50.7 1
 
2.0%
49.5 1
 
2.0%
Other values (31) 31
62.0%
ValueCountFrequency (%)
33.1 1
2.0%
40.7 1
2.0%
42.6 1
2.0%
42.8 1
2.0%
44.2 1
2.0%
45.7 1
2.0%
46.1 2
4.0%
47.6 1
2.0%
47.7 1
2.0%
48.4 1
2.0%
ValueCountFrequency (%)
59.5 1
2.0%
57.1 1
2.0%
55.6 1
2.0%
55.1 1
2.0%
54.6 1
2.0%
54.4 1
2.0%
53.3 1
2.0%
52.9 2
4.0%
52.7 2
4.0%
52.5 1
2.0%

전반적인 여가활동 약간 만족 (퍼센트)
Real number (ℝ)

HIGH CORRELATION 

Distinct43
Distinct (%)86.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11.16
Minimum4.6
Maximum19.8
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size582.0 B
2024-03-18T11:27:52.761082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4.6
5-th percentile6.835
Q19.25
median10.95
Q312.9
95-th percentile16.225
Maximum19.8
Range15.2
Interquartile range (IQR)3.65

Descriptive statistics

Standard deviation2.9862269
Coefficient of variation (CV)0.26758305
Kurtosis0.54718829
Mean11.16
Median Absolute Deviation (MAD)1.95
Skewness0.39300333
Sum558
Variance8.917551
MonotonicityNot monotonic
2024-03-18T11:27:52.891975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=43)
ValueCountFrequency (%)
8.0 2
 
4.0%
11.8 2
 
4.0%
13.6 2
 
4.0%
12.9 2
 
4.0%
9.4 2
 
4.0%
10.5 2
 
4.0%
10.7 2
 
4.0%
15.1 1
 
2.0%
14.1 1
 
2.0%
8.7 1
 
2.0%
Other values (33) 33
66.0%
ValueCountFrequency (%)
4.6 1
2.0%
6.0 1
2.0%
6.7 1
2.0%
7.0 1
2.0%
7.3 1
2.0%
7.5 1
2.0%
8.0 2
4.0%
8.4 1
2.0%
8.7 1
2.0%
8.8 1
2.0%
ValueCountFrequency (%)
19.8 1
2.0%
17.0 1
2.0%
16.9 1
2.0%
15.4 1
2.0%
15.1 1
2.0%
14.8 1
2.0%
14.1 1
2.0%
14.0 1
2.0%
13.6 2
4.0%
13.3 1
2.0%

전반적인 여가활동 매우 만족 (퍼센트)
Real number (ℝ)

HIGH CORRELATION 

Distinct21
Distinct (%)42.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.56
Minimum0.6
Maximum3.7
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size582.0 B
2024-03-18T11:27:52.996253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.6
5-th percentile0.6
Q11.2
median1.5
Q31.9
95-th percentile2.5
Maximum3.7
Range3.1
Interquartile range (IQR)0.7

Descriptive statistics

Standard deviation0.67005939
Coefficient of variation (CV)0.42952525
Kurtosis2.1475813
Mean1.56
Median Absolute Deviation (MAD)0.35
Skewness1.1083651
Sum78
Variance0.44897959
MonotonicityNot monotonic
2024-03-18T11:27:53.099676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
1.2 9
18.0%
1.6 6
12.0%
1.5 4
 
8.0%
0.6 4
 
8.0%
1.9 3
 
6.0%
2.0 2
 
4.0%
0.7 2
 
4.0%
1.8 2
 
4.0%
1.7 2
 
4.0%
2.5 2
 
4.0%
Other values (11) 14
28.0%
ValueCountFrequency (%)
0.6 4
8.0%
0.7 2
 
4.0%
0.8 1
 
2.0%
0.9 1
 
2.0%
1.0 1
 
2.0%
1.1 2
 
4.0%
1.2 9
18.0%
1.3 1
 
2.0%
1.4 1
 
2.0%
1.5 4
8.0%
ValueCountFrequency (%)
3.7 1
 
2.0%
3.6 1
 
2.0%
2.5 2
4.0%
2.4 2
4.0%
2.2 1
 
2.0%
2.1 2
4.0%
2.0 2
4.0%
1.9 3
6.0%
1.8 2
4.0%
1.7 2
4.0%

전반적인 여가활동 5점 평균 (점)
Real number (ℝ)

HIGH CORRELATION 

Distinct25
Distinct (%)50.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.7112
Minimum2.33
Maximum2.93
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size582.0 B
2024-03-18T11:27:53.192548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.33
5-th percentile2.538
Q12.67
median2.73
Q32.78
95-th percentile2.83
Maximum2.93
Range0.6
Interquartile range (IQR)0.11

Descriptive statistics

Standard deviation0.10582311
Coefficient of variation (CV)0.039031835
Kurtosis3.2987624
Mean2.7112
Median Absolute Deviation (MAD)0.055
Skewness-1.2513594
Sum135.56
Variance0.011198531
MonotonicityNot monotonic
2024-03-18T11:27:53.299586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
2.73 7
14.0%
2.7 4
 
8.0%
2.74 4
 
8.0%
2.67 3
 
6.0%
2.78 3
 
6.0%
2.79 3
 
6.0%
2.8 3
 
6.0%
2.83 2
 
4.0%
2.63 2
 
4.0%
2.68 2
 
4.0%
Other values (15) 17
34.0%
ValueCountFrequency (%)
2.33 1
 
2.0%
2.42 1
 
2.0%
2.52 1
 
2.0%
2.56 1
 
2.0%
2.58 1
 
2.0%
2.61 2
4.0%
2.63 2
4.0%
2.65 2
4.0%
2.67 3
6.0%
2.68 2
4.0%
ValueCountFrequency (%)
2.93 1
 
2.0%
2.9 1
 
2.0%
2.83 2
4.0%
2.82 1
 
2.0%
2.8 3
6.0%
2.79 3
6.0%
2.78 3
6.0%
2.77 1
 
2.0%
2.76 1
 
2.0%
2.75 1
 
2.0%

Interactions

2024-03-18T11:27:48.143217image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:27:36.828964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:27:37.760898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:27:38.921045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:27:39.883957image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:27:40.829488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:27:41.771522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:27:42.726899image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:27:43.605512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:27:44.756558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:27:45.721145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:27:47.050653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:27:48.212120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:27:36.892255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:27:37.832385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:27:39.018639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:27:39.954463image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:27:40.894673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:27:41.853938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:27:42.790373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:27:43.682144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:27:44.831871image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:27:45.796012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:27:47.125079image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:27:48.278643image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:27:36.966164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:27:37.898660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:27:39.094247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:27:40.028713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:27:40.959862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:27:41.925020image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:27:42.854313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:27:43.752077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:27:44.904327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:27:45.890879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:27:47.196042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:27:48.367092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:27:37.039864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:27:37.973200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:27:39.160277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:27:40.105145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:27:41.055153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:27:41.994733image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:27:42.927471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:27:43.815703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:27:44.986028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:27:45.981669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:27:47.287611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:27:48.476744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:27:37.125425image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:27:38.049948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:27:39.237671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:27:40.183655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:27:41.175110image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:27:42.071750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:27:42.998807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:27:44.154301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:27:45.073991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:27:46.189068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:27:47.380014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:27:48.556987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:27:37.188716image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:27:38.112880image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:27:39.305255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:27:40.257805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:27:41.251702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:27:42.145294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:27:43.062795image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:27:44.215332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:27:45.140694image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:27:46.345021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:27:47.461303image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:27:48.644965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:27:37.266740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:27:38.186518image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:27:39.391023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:27:40.342686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:27:41.336819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:27:42.228601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:27:43.136839image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:27:44.288852image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:27:45.222682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:27:46.493395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:27:47.583150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:27:48.722340image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:27:37.343376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:27:38.260355image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:27:39.464659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:27:40.420439image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:27:41.409303image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:27:42.304166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:27:43.218618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:27:44.352392image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:27:45.292071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:27:46.584099image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:27:47.692456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:27:48.794891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:27:37.425056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:27:38.329001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:27:39.544877image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:27:40.489883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:27:41.475143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:27:42.386225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:27:43.318331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:27:44.425327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:27:45.370006image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:27:46.703475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:27:47.797422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:27:48.868407image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:27:37.520630image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:27:38.408064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:27:39.639469image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:27:40.572588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:27:41.542843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:27:42.485001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:27:43.396870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:27:44.497010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:27:45.467328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:27:46.789123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:27:47.876678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:27:48.954161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:27:37.606262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:27:38.491279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:27:39.732927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:27:40.661117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:27:41.617065image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:27:42.571378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:27:43.466636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:27:44.585188image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:27:45.575238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:27:46.887519image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:27:47.965775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:27:49.025187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:27:37.689361image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:27:38.568467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:27:39.809150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:27:40.745905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:27:41.687744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:27:42.648347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:27:43.536522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:27:44.676218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:27:45.650568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:27:46.966475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:27:48.060725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-18T11:27:53.391148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
특성별(1)특성별(2)문화여가시설(접근성과 충분 정도) 매우 불만족 (퍼센트)문화여가시설(접근성과 충분 정도) 약간 불만족 (퍼센트)문화여가시설(접근성과 충분 정도) 보통 (퍼센트)문화여가시설(접근성과 충분 정도) 약간 만족 (퍼센트)문화여가시설(접근성과 충분 정도) 매우 만족 (퍼센트)문화여가시설(접근성과 충분 정도) 5점 평균 (점)전반적인 여가활동 매우 불만족 (퍼센트)전반적인 여가활동 약간 불만족 (퍼센트)전반적인 여가활동 보통 (퍼센트)전반적인 여가활동 약간 만족 (퍼센트)전반적인 여가활동 매우 만족 (퍼센트)전반적인 여가활동 5점 평균 (점)
특성별(1)1.0001.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.000
특성별(2)1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
문화여가시설(접근성과 충분 정도) 매우 불만족 (퍼센트)0.0001.0001.0000.6560.8390.5480.3240.8920.9330.5020.8140.3470.3980.891
문화여가시설(접근성과 충분 정도) 약간 불만족 (퍼센트)0.0001.0000.6561.0000.6250.5950.6780.7680.6740.8600.6420.6210.1290.785
문화여가시설(접근성과 충분 정도) 보통 (퍼센트)0.0001.0000.8390.6251.0000.7560.6470.9210.8270.5330.9750.5100.3550.879
문화여가시설(접근성과 충분 정도) 약간 만족 (퍼센트)0.0001.0000.5480.5950.7561.0000.7360.8680.3260.8240.7920.8780.5550.853
문화여가시설(접근성과 충분 정도) 매우 만족 (퍼센트)0.0001.0000.3240.6780.6470.7361.0000.6460.3980.5680.3890.6650.8400.680
문화여가시설(접근성과 충분 정도) 5점 평균 (점)0.0001.0000.8920.7680.9210.8680.6461.0000.8960.7780.8820.7390.5260.980
전반적인 여가활동 매우 불만족 (퍼센트)0.0001.0000.9330.6740.8270.3260.3980.8961.0000.4820.7800.5050.3750.890
전반적인 여가활동 약간 불만족 (퍼센트)0.0001.0000.5020.8600.5330.8240.5680.7780.4821.0000.6790.5620.0000.848
전반적인 여가활동 보통 (퍼센트)0.0001.0000.8140.6420.9750.7920.3890.8820.7800.6791.0000.7010.4020.904
전반적인 여가활동 약간 만족 (퍼센트)0.0001.0000.3470.6210.5100.8780.6650.7390.5050.5620.7011.0000.5580.710
전반적인 여가활동 매우 만족 (퍼센트)0.0001.0000.3980.1290.3550.5550.8400.5260.3750.0000.4020.5581.0000.734
전반적인 여가활동 5점 평균 (점)0.0001.0000.8910.7850.8790.8530.6800.9800.8900.8480.9040.7100.7341.000
2024-03-18T11:27:53.550360image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
문화여가시설(접근성과 충분 정도) 매우 불만족 (퍼센트)문화여가시설(접근성과 충분 정도) 약간 불만족 (퍼센트)문화여가시설(접근성과 충분 정도) 보통 (퍼센트)문화여가시설(접근성과 충분 정도) 약간 만족 (퍼센트)문화여가시설(접근성과 충분 정도) 매우 만족 (퍼센트)문화여가시설(접근성과 충분 정도) 5점 평균 (점)전반적인 여가활동 매우 불만족 (퍼센트)전반적인 여가활동 약간 불만족 (퍼센트)전반적인 여가활동 보통 (퍼센트)전반적인 여가활동 약간 만족 (퍼센트)전반적인 여가활동 매우 만족 (퍼센트)전반적인 여가활동 5점 평균 (점)특성별(1)
문화여가시설(접근성과 충분 정도) 매우 불만족 (퍼센트)1.000-0.016-0.080-0.314-0.005-0.3820.962-0.065-0.124-0.264-0.049-0.3620.000
문화여가시설(접근성과 충분 정도) 약간 불만족 (퍼센트)-0.0161.000-0.500-0.606-0.522-0.7780.0570.918-0.471-0.632-0.545-0.7970.000
문화여가시설(접근성과 충분 정도) 보통 (퍼센트)-0.080-0.5001.000-0.0390.1100.242-0.085-0.5140.8260.006-0.0340.2700.000
문화여가시설(접근성과 충분 정도) 약간 만족 (퍼센트)-0.314-0.606-0.0391.0000.5430.915-0.387-0.505-0.0740.9580.6480.9040.000
문화여가시설(접근성과 충분 정도) 매우 만족 (퍼센트)-0.005-0.5220.1100.5431.0000.606-0.008-0.4880.1930.4710.8100.5740.000
문화여가시설(접근성과 충분 정도) 5점 평균 (점)-0.382-0.7780.2420.9150.6061.000-0.456-0.6600.2150.8970.6540.9810.000
전반적인 여가활동 매우 불만족 (퍼센트)0.9620.057-0.085-0.387-0.008-0.4561.000-0.010-0.117-0.350-0.066-0.4360.000
전반적인 여가활동 약간 불만족 (퍼센트)-0.0650.918-0.514-0.505-0.488-0.660-0.0101.000-0.574-0.552-0.421-0.7110.000
전반적인 여가활동 보통 (퍼센트)-0.124-0.4710.826-0.0740.1930.215-0.117-0.5741.000-0.050-0.0190.2680.000
전반적인 여가활동 약간 만족 (퍼센트)-0.264-0.6320.0060.9580.4710.897-0.350-0.552-0.0501.0000.5740.9130.000
전반적인 여가활동 매우 만족 (퍼센트)-0.049-0.545-0.0340.6480.8100.654-0.066-0.421-0.0190.5741.0000.6430.000
전반적인 여가활동 5점 평균 (점)-0.362-0.7970.2700.9040.5740.981-0.436-0.7110.2680.9130.6431.0000.000
특성별(1)0.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0001.000

Missing values

2024-03-18T11:27:49.141235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-18T11:27:49.581471image/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

특성별(1)특성별(2)문화여가시설(접근성과 충분 정도) 매우 불만족 (퍼센트)문화여가시설(접근성과 충분 정도) 약간 불만족 (퍼센트)문화여가시설(접근성과 충분 정도) 보통 (퍼센트)문화여가시설(접근성과 충분 정도) 약간 만족 (퍼센트)문화여가시설(접근성과 충분 정도) 매우 만족 (퍼센트)문화여가시설(접근성과 충분 정도) 5점 평균 (점)전반적인 여가활동 매우 불만족 (퍼센트)전반적인 여가활동 약간 불만족 (퍼센트)전반적인 여가활동 보통 (퍼센트)전반적인 여가활동 약간 만족 (퍼센트)전반적인 여가활동 매우 만족 (퍼센트)전반적인 여가활동 5점 평균 (점)
0군구별중구2.947.444.74.60.42.522.439.652.94.60.62.61
1군구별동구7.830.753.37.60.52.627.227.755.68.80.62.68
2군구별미추홀구4.432.755.56.70.82.674.628.559.56.70.62.7
3군구별연수구6.528.840.120.24.52.876.728.146.117.02.12.8
4군구별남동구2.946.342.17.61.02.572.846.242.67.31.22.58
5군구별부평구8.127.050.612.12.32.737.325.652.911.82.42.76
6군구별계양구1.231.343.123.21.12.921.234.740.719.83.62.9
7군구별서구5.524.756.512.01.32.794.723.757.113.21.22.82
8군구별강화군18.431.241.77.31.32.4218.830.042.87.01.52.42
9군구별옹진군17.540.034.67.50.42.3311.934.244.28.90.72.52
특성별(1)특성별(2)문화여가시설(접근성과 충분 정도) 매우 불만족 (퍼센트)문화여가시설(접근성과 충분 정도) 약간 불만족 (퍼센트)문화여가시설(접근성과 충분 정도) 보통 (퍼센트)문화여가시설(접근성과 충분 정도) 약간 만족 (퍼센트)문화여가시설(접근성과 충분 정도) 매우 만족 (퍼센트)문화여가시설(접근성과 충분 정도) 5점 평균 (점)전반적인 여가활동 매우 불만족 (퍼센트)전반적인 여가활동 약간 불만족 (퍼센트)전반적인 여가활동 보통 (퍼센트)전반적인 여가활동 약간 만족 (퍼센트)전반적인 여가활동 매우 만족 (퍼센트)전반적인 여가활동 5점 평균 (점)
40주거형태별연립/다세대주택4.836.248.39.61.12.664.435.649.49.41.22.67
41주거형태별기타6.834.246.811.11.22.665.733.549.510.50.72.67
42주거점유형태별자가5.532.348.212.31.72.725.130.950.711.61.62.74
43주거점유형태별전세4.532.348.013.41.82.764.032.148.713.31.92.77
44주거점유형태별월세 및 기타5.835.348.39.31.32.656.033.650.88.41.22.65
45가구원수별1인5.135.548.09.91.52.675.234.050.09.41.42.68
46가구원수별2인4.636.047.010.71.82.694.534.249.79.91.62.7
47가구원수별3인5.631.847.613.41.72.745.230.649.812.51.92.75
48가구원수별4인5.331.848.512.91.52.744.831.350.312.31.22.74
49가구원수별5인 이상6.827.652.111.52.02.746.125.654.411.92.12.78