Overview

Dataset statistics

Number of variables8
Number of observations50
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.5 KiB
Average record size in memory72.6 B

Variable types

Categorical1
Text1
Numeric6

Dataset

Description대중교통 이용만족도 중 택시에 대한 이용여부 만족도를 표시하고 있습니다.* 특성별(1) 특성별(2) 택시 이용함 택시 이용하지 않음 매우 만족 (%) 약간 만족 (%) 보통 (%) 약간 불만족 (%) 매우 불만족 (%) 5점 평균 (점)
Author인천광역시
URLhttps://www.data.go.kr/data/15066427/fileData.do

Alerts

택시 약간 불만족 (퍼센트) is highly overall correlated with 택시 약간 만족 (퍼센트) and 1 other fieldsHigh correlation
택시 약간 만족 (퍼센트) is highly overall correlated with 택시 약간 불만족 (퍼센트) and 1 other fieldsHigh correlation
택시 5점 평균 (점) is highly overall correlated with 택시 약간 불만족 (퍼센트) and 1 other fieldsHigh correlation
특성별(2) has unique valuesUnique

Reproduction

Analysis started2023-12-23 06:44:18.603687
Analysis finished2023-12-23 06:44:36.390541
Duration17.79 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
8 
월평균소득별
8 
연령별
6 
가구원수별
5 
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

2023-12-23T06:44:36.739433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-23T06:44:37.343093image/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
2023-12-23T06:44:37.806599image/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%
2023-12-23T06:44:38.737803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 33
 
13.4%
22
 
8.9%
만 15
 
6.1%
~ 11
 
4.5%
세 9
 
3.7%
원 8
 
3.3%
구 8
 
3.3%
미 8
 
3.3%
3 6
 
2.4%
인 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 (%)
만 15
 
10.6%
세 9
 
6.3%
원 8
 
5.6%
구 8
 
5.6%
미 8
 
5.6%
인 5
 
3.5%
이 5
 
3.5%
상 4
 
2.8%
기 4
 
2.8%
졸 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 (%)
만 15
 
10.6%
세 9
 
6.3%
원 8
 
5.6%
구 8
 
5.6%
미 8
 
5.6%
인 5
 
3.5%
이 5
 
3.5%
상 4
 
2.8%
기 4
 
2.8%
졸 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 (%)
만 15
 
10.6%
세 9
 
6.3%
원 8
 
5.6%
구 8
 
5.6%
미 8
 
5.6%
인 5
 
3.5%
이 5
 
3.5%
상 4
 
2.8%
기 4
 
2.8%
졸 4
 
2.8%
Other values (54) 72
50.7%

택시 매우 불만족 (퍼센트)
Real number (ℝ)

Distinct26
Distinct (%)52.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.046
Minimum0.5
Maximum11.6
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size582.0 B
2023-12-23T06:44:39.213532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.5
5-th percentile1.035
Q12.325
median2.7
Q33.275
95-th percentile5.365
Maximum11.6
Range11.1
Interquartile range (IQR)0.95

Descriptive statistics

Standard deviation1.9555478
Coefficient of variation (CV)0.6420052
Kurtosis11.671416
Mean3.046
Median Absolute Deviation (MAD)0.45
Skewness3.092249
Sum152.3
Variance3.8241673
MonotonicityNot monotonic
2023-12-23T06:44:39.652962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
2.7 5
 
10.0%
2.5 4
 
8.0%
3.0 4
 
8.0%
2.8 4
 
8.0%
3.3 3
 
6.0%
2.3 3
 
6.0%
4.1 3
 
6.0%
2.4 3
 
6.0%
1.5 2
 
4.0%
3.2 2
 
4.0%
Other values (16) 17
34.0%
ValueCountFrequency (%)
0.5 1
 
2.0%
0.6 1
 
2.0%
0.9 1
 
2.0%
1.2 1
 
2.0%
1.5 2
4.0%
1.6 1
 
2.0%
1.7 1
 
2.0%
2.0 1
 
2.0%
2.2 1
 
2.0%
2.3 3
6.0%
ValueCountFrequency (%)
11.6 1
 
2.0%
10.9 1
 
2.0%
6.4 1
 
2.0%
4.1 3
6.0%
3.9 1
 
2.0%
3.7 1
 
2.0%
3.5 2
4.0%
3.3 3
6.0%
3.2 2
4.0%
3.1 1
 
2.0%

택시 약간 불만족 (퍼센트)
Real number (ℝ)

HIGH CORRELATION 

Distinct31
Distinct (%)62.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean10.042
Minimum1.9
Maximum25.3
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size582.0 B
2023-12-23T06:44:40.067975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.9
5-th percentile7.34
Q18.725
median9.55
Q310.175
95-th percentile15.915
Maximum25.3
Range23.4
Interquartile range (IQR)1.45

Descriptive statistics

Standard deviation3.2987994
Coefficient of variation (CV)0.32850024
Kurtosis10.351705
Mean10.042
Median Absolute Deviation (MAD)0.75
Skewness2.4514264
Sum502.1
Variance10.882078
MonotonicityNot monotonic
2023-12-23T06:44:40.734845image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
8.4 5
 
10.0%
10.0 4
 
8.0%
9.8 3
 
6.0%
8.8 3
 
6.0%
9.7 2
 
4.0%
9.4 2
 
4.0%
10.9 2
 
4.0%
9.1 2
 
4.0%
8.7 2
 
4.0%
8.9 2
 
4.0%
Other values (21) 23
46.0%
ValueCountFrequency (%)
1.9 1
 
2.0%
6.1 1
 
2.0%
6.8 1
 
2.0%
8.0 1
 
2.0%
8.4 5
10.0%
8.5 1
 
2.0%
8.6 1
 
2.0%
8.7 2
 
4.0%
8.8 3
6.0%
8.9 2
 
4.0%
ValueCountFrequency (%)
25.3 1
2.0%
19.5 1
2.0%
16.5 1
2.0%
15.2 1
2.0%
12.6 1
2.0%
11.7 1
2.0%
11.2 1
2.0%
10.9 2
4.0%
10.5 2
4.0%
10.2 2
4.0%

택시 보통 (퍼센트)
Real number (ℝ)

Distinct36
Distinct (%)72.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean46.146
Minimum30
Maximum62.4
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size582.0 B
2023-12-23T06:44:41.404769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum30
5-th percentile35.31
Q145.4
median46.35
Q347.3
95-th percentile50.46
Maximum62.4
Range32.4
Interquartile range (IQR)1.9

Descriptive statistics

Standard deviation4.9810338
Coefficient of variation (CV)0.10794075
Kurtosis4.8405327
Mean46.146
Median Absolute Deviation (MAD)1
Skewness-0.50862901
Sum2307.3
Variance24.810698
MonotonicityNot monotonic
2023-12-23T06:44:42.195584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=36)
ValueCountFrequency (%)
46.3 5
 
10.0%
49.4 3
 
6.0%
46.4 3
 
6.0%
47.2 3
 
6.0%
47.3 2
 
4.0%
45.0 2
 
4.0%
49.1 2
 
4.0%
46.1 2
 
4.0%
51.0 1
 
2.0%
45.7 1
 
2.0%
Other values (26) 26
52.0%
ValueCountFrequency (%)
30.0 1
2.0%
33.0 1
2.0%
34.5 1
2.0%
36.3 1
2.0%
42.3 1
2.0%
43.1 1
2.0%
43.9 1
2.0%
44.2 1
2.0%
44.4 1
2.0%
44.8 1
2.0%
ValueCountFrequency (%)
62.4 1
 
2.0%
57.6 1
 
2.0%
51.0 1
 
2.0%
49.8 1
 
2.0%
49.5 1
 
2.0%
49.4 3
6.0%
49.1 2
4.0%
48.3 1
 
2.0%
47.4 1
 
2.0%
47.3 2
4.0%

택시 약간 만족 (퍼센트)
Real number (ℝ)

HIGH CORRELATION 

Distinct37
Distinct (%)74.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean30.222
Minimum9.1
Maximum53.3
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size582.0 B
2023-12-23T06:44:43.255398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum9.1
5-th percentile20.575
Q128.925
median30.25
Q331.45
95-th percentile36.945
Maximum53.3
Range44.2
Interquartile range (IQR)2.525

Descriptive statistics

Standard deviation6.2432752
Coefficient of variation (CV)0.20658048
Kurtosis6.7808743
Mean30.222
Median Absolute Deviation (MAD)1.3
Skewness0.52345782
Sum1511.1
Variance38.978486
MonotonicityNot monotonic
2023-12-23T06:44:44.082000image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=37)
ValueCountFrequency (%)
30.9 4
 
8.0%
29.0 3
 
6.0%
32.2 3
 
6.0%
31.1 2
 
4.0%
27.1 2
 
4.0%
30.1 2
 
4.0%
30.8 2
 
4.0%
29.1 2
 
4.0%
32.5 2
 
4.0%
30.6 1
 
2.0%
Other values (27) 27
54.0%
ValueCountFrequency (%)
9.1 1
2.0%
17.4 1
2.0%
19.0 1
2.0%
22.5 1
2.0%
25.3 1
2.0%
27.1 2
4.0%
27.5 1
2.0%
28.0 1
2.0%
28.2 1
2.0%
28.6 1
2.0%
ValueCountFrequency (%)
53.3 1
 
2.0%
48.9 1
 
2.0%
37.8 1
 
2.0%
35.9 1
 
2.0%
35.2 1
 
2.0%
33.3 1
 
2.0%
32.5 2
4.0%
32.2 3
6.0%
31.9 1
 
2.0%
31.5 1
 
2.0%

택시 매우 만족 (퍼센트)
Real number (ℝ)

Distinct38
Distinct (%)76.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean10.554
Minimum1.9
Maximum25.2
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size582.0 B
2023-12-23T06:44:44.860628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.9
5-th percentile6.025
Q19.45
median10.4
Q311.2
95-th percentile15.62
Maximum25.2
Range23.3
Interquartile range (IQR)1.75

Descriptive statistics

Standard deviation3.3788786
Coefficient of variation (CV)0.32015147
Kurtosis7.6533883
Mean10.554
Median Absolute Deviation (MAD)0.85
Skewness1.5205643
Sum527.7
Variance11.41682
MonotonicityNot monotonic
2023-12-23T06:44:45.618406image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=38)
ValueCountFrequency (%)
10.9 3
 
6.0%
10.8 3
 
6.0%
9.8 2
 
4.0%
10.0 2
 
4.0%
9.6 2
 
4.0%
9.4 2
 
4.0%
9.7 2
 
4.0%
10.5 2
 
4.0%
8.7 2
 
4.0%
11.2 2
 
4.0%
Other values (28) 28
56.0%
ValueCountFrequency (%)
1.9 1
2.0%
3.7 1
2.0%
4.9 1
2.0%
7.4 1
2.0%
7.5 1
2.0%
8.0 1
2.0%
8.7 2
4.0%
8.8 1
2.0%
9.0 1
2.0%
9.2 1
2.0%
ValueCountFrequency (%)
25.2 1
2.0%
18.7 1
2.0%
16.7 1
2.0%
14.3 1
2.0%
13.7 1
2.0%
12.6 1
2.0%
12.1 1
2.0%
12.0 1
2.0%
11.8 1
2.0%
11.7 1
2.0%

택시 5점 평균 (점)
Real number (ℝ)

HIGH CORRELATION 

Distinct7
Distinct (%)14.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.358
Minimum2.9
Maximum3.8
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size582.0 B
2023-12-23T06:44:46.424028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.9
5-th percentile3.245
Q13.3
median3.4
Q33.4
95-th percentile3.455
Maximum3.8
Range0.9
Interquartile range (IQR)0.1

Descriptive statistics

Standard deviation0.11967643
Coefficient of variation (CV)0.0356392
Kurtosis8.0860441
Mean3.358
Median Absolute Deviation (MAD)0
Skewness-0.68050641
Sum167.9
Variance0.014322449
MonotonicityNot monotonic
2023-12-23T06:44:47.478874image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
3.4 28
56.0%
3.3 16
32.0%
3.5 2
 
4.0%
3.0 1
 
2.0%
3.8 1
 
2.0%
3.2 1
 
2.0%
2.9 1
 
2.0%
ValueCountFrequency (%)
2.9 1
 
2.0%
3.0 1
 
2.0%
3.2 1
 
2.0%
3.3 16
32.0%
3.4 28
56.0%
3.5 2
 
4.0%
3.8 1
 
2.0%
ValueCountFrequency (%)
3.8 1
 
2.0%
3.5 2
 
4.0%
3.4 28
56.0%
3.3 16
32.0%
3.2 1
 
2.0%
3.0 1
 
2.0%
2.9 1
 
2.0%

Interactions

2023-12-23T06:44:32.570611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-23T06:44:19.709616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-23T06:44:22.191308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-23T06:44:24.459023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-23T06:44:27.745760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-23T06:44:29.977318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-23T06:44:33.136928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-23T06:44:20.071552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-23T06:44:22.464782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-23T06:44:24.956910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-23T06:44:28.276015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-23T06:44:30.402027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-23T06:44:33.645144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-23T06:44:20.377859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-23T06:44:22.714234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-23T06:44:25.532496image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-23T06:44:28.770122image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-23T06:44:30.845889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-23T06:44:34.211816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-23T06:44:20.973393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-23T06:44:23.083267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-23T06:44:26.049113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-23T06:44:29.100040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-23T06:44:31.277015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-23T06:44:34.571333image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-23T06:44:21.284976image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-23T06:44:23.650947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-23T06:44:26.447725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-23T06:44:29.330674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-23T06:44:31.697495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-23T06:44:35.014418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-23T06:44:21.604091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-23T06:44:24.101848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-23T06:44:27.445596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-23T06:44:29.638119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-23T06:44:32.114749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-23T06:44:47.984256image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
특성별(1)특성별(2)택시 매우 불만족 (퍼센트)택시 약간 불만족 (퍼센트)택시 보통 (퍼센트)택시 약간 만족 (퍼센트)택시 매우 만족 (퍼센트)택시 5점 평균 (점)
특성별(1)1.0001.0000.0000.0000.0000.0000.0000.000
특성별(2)1.0001.0001.0001.0001.0001.0001.0001.000
택시 매우 불만족 (퍼센트)0.0001.0001.0000.7150.6540.4980.6780.636
택시 약간 불만족 (퍼센트)0.0001.0000.7151.0000.8670.9170.9550.934
택시 보통 (퍼센트)0.0001.0000.6540.8671.0000.9630.7390.852
택시 약간 만족 (퍼센트)0.0001.0000.4980.9170.9631.0000.8640.868
택시 매우 만족 (퍼센트)0.0001.0000.6780.9550.7390.8641.0000.887
택시 5점 평균 (점)0.0001.0000.6360.9340.8520.8680.8871.000
2023-12-23T06:44:48.668385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
택시 매우 불만족 (퍼센트)택시 약간 불만족 (퍼센트)택시 보통 (퍼센트)택시 약간 만족 (퍼센트)택시 매우 만족 (퍼센트)택시 5점 평균 (점)특성별(1)
택시 매우 불만족 (퍼센트)1.0000.197-0.267-0.097-0.186-0.3850.000
택시 약간 불만족 (퍼센트)0.1971.000-0.155-0.512-0.066-0.5090.000
택시 보통 (퍼센트)-0.267-0.1551.000-0.346-0.261-0.3080.000
택시 약간 만족 (퍼센트)-0.097-0.512-0.3461.000-0.1520.5950.000
택시 매우 만족 (퍼센트)-0.186-0.066-0.261-0.1521.0000.4610.000
택시 5점 평균 (점)-0.385-0.509-0.3080.5950.4611.0000.000
특성별(1)0.0000.0000.0000.0000.0000.0001.000

Missing values

2023-12-23T06:44:35.513478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-23T06:44:36.078093image/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)택시 매우 불만족 (퍼센트)택시 약간 불만족 (퍼센트)택시 보통 (퍼센트)택시 약간 만족 (퍼센트)택시 매우 만족 (퍼센트)택시 5점 평균 (점)
0군구별중구3.311.233.048.93.73.4
1군구별동구3.06.142.337.810.83.5
2군구별미추홀구1.515.262.419.01.93.0
3군구별연수구1.28.457.625.37.53.3
4군구별남동구0.68.446.328.016.73.5
5군구별부평구3.58.446.132.59.63.4
6군구별계양구0.51.930.053.314.33.8
7군구별서구6.410.244.829.09.73.3
8군구별강화군11.619.534.59.125.23.2
9군구별옹진군3.516.543.917.418.73.3
특성별(1)특성별(2)택시 매우 불만족 (퍼센트)택시 약간 불만족 (퍼센트)택시 보통 (퍼센트)택시 약간 만족 (퍼센트)택시 매우 만족 (퍼센트)택시 5점 평균 (점)
40주거형태별연립/다세대주택2.59.845.730.811.23.4
41주거형태별기타1.69.151.030.97.43.3
42주거점유형태별자가2.79.347.230.810.03.4
43주거점유형태별전세3.710.045.330.610.53.3
44주거점유형태별월세 및 기타2.09.647.030.211.33.4
45가구원수별1인2.210.946.130.110.63.4
46가구원수별2인2.39.947.229.211.43.4
47가구원수별3인3.39.446.431.19.83.3
48가구원수별4인2.38.646.332.210.53.4
49가구원수별5인 이상4.18.849.829.38.03.3