Overview

Dataset statistics

Number of variables6
Number of observations155
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory8.0 KiB
Average record size in memory52.9 B

Variable types

Categorical3
Numeric3

Dataset

Description경기도 청소년 교통비 지원금 지급현황
Author경기교통공사
URLhttps://data.gg.go.kr/portal/data/service/selectServicePage.do?&infId=ZKJG9F06DBLENP8GUD7332992879&infSeq=1

Alerts

지급자(명) is highly overall correlated with 신청자(명) and 1 other fieldsHigh correlation
1인평균지급금액(원) is highly overall correlated with 반기구분High correlation
신청자(명) is highly overall correlated with 지급자(명) and 1 other fieldsHigh correlation
반기구분 is highly overall correlated with 1인평균지급금액(원)High correlation
시군명 is highly overall correlated with 지급자(명) and 1 other fieldsHigh correlation
지급자(명) has unique valuesUnique
1인평균지급금액(원) has unique valuesUnique

Reproduction

Analysis started2024-04-20 18:35:53.548476
Analysis finished2024-04-20 18:35:55.726595
Duration2.18 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

기준년도
Categorical

Distinct3
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2022
62 
2021
62 
2023
31 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023
2nd row2023
3rd row2023
4th row2023
5th row2023

Common Values

ValueCountFrequency (%)
2022 62
40.0%
2021 62
40.0%
2023 31
20.0%

Length

2024-04-21T03:35:55.779660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T03:35:55.862895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2022 62
40.0%
2021 62
40.0%
2023 31
20.0%

반기구분
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
상반기
93 
하반기
62 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
상반기 93
60.0%
하반기 62
40.0%

Length

2024-04-21T03:35:55.947894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T03:35:56.027909image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
상반기 93
60.0%
하반기 62
40.0%

시군명
Categorical

HIGH CORRELATION 

Distinct31
Distinct (%)20.0%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
수원시
 
5
연천군
 
5
고양시
 
5
성남시
 
5
부천시
 
5
Other values (26)
130 

Length

Max length4
Median length3
Mean length3.0967742
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row수원시
2nd row연천군
3rd row고양시
4th row성남시
5th row부천시

Common Values

ValueCountFrequency (%)
수원시 5
 
3.2%
연천군 5
 
3.2%
고양시 5
 
3.2%
성남시 5
 
3.2%
부천시 5
 
3.2%
화성시 5
 
3.2%
안산시 5
 
3.2%
남양주시 5
 
3.2%
안양시 5
 
3.2%
평택시 5
 
3.2%
Other values (21) 105
67.7%

Length

2024-04-21T03:35:56.111778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
수원시 5
 
3.2%
군포시 5
 
3.2%
과천시 5
 
3.2%
가평군 5
 
3.2%
동두천시 5
 
3.2%
여주시 5
 
3.2%
양평군 5
 
3.2%
의왕시 5
 
3.2%
포천시 5
 
3.2%
안성시 5
 
3.2%
Other values (21) 105
67.7%

지급자(명)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct155
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean15116.219
Minimum440
Maximum54809
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2024-04-21T03:35:56.216654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum440
5-th percentile802.8
Q15570.5
median12759
Q320117.5
95-th percentile42571.6
Maximum54809
Range54369
Interquartile range (IQR)14547

Descriptive statistics

Standard deviation12732.641
Coefficient of variation (CV)0.84231652
Kurtosis0.54901114
Mean15116.219
Median Absolute Deviation (MAD)7262
Skewness1.0684876
Sum2343014
Variance1.6212016 × 108
MonotonicityNot monotonic
2024-04-21T03:35:56.329167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
47460 1
 
0.6%
14439 1
 
0.6%
24898 1
 
0.6%
16879 1
 
0.6%
19139 1
 
0.6%
15830 1
 
0.6%
16631 1
 
0.6%
17112 1
 
0.6%
14354 1
 
0.6%
12576 1
 
0.6%
Other values (145) 145
93.5%
ValueCountFrequency (%)
440 1
0.6%
538 1
0.6%
565 1
0.6%
627 1
0.6%
630 1
0.6%
711 1
0.6%
737 1
0.6%
800 1
0.6%
804 1
0.6%
975 1
0.6%
ValueCountFrequency (%)
54809 1
0.6%
51430 1
0.6%
49168 1
0.6%
47460 1
0.6%
45580 1
0.6%
45029 1
0.6%
44635 1
0.6%
43098 1
0.6%
42346 1
0.6%
41284 1
0.6%

1인평균지급금액(원)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct155
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean48192.948
Minimum33720
Maximum60871
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2024-04-21T03:35:56.440725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum33720
5-th percentile38071.6
Q144381
median46706
Q353909.5
95-th percentile57844.9
Maximum60871
Range27151
Interquartile range (IQR)9528.5

Descriptive statistics

Standard deviation6105.8538
Coefficient of variation (CV)0.126696
Kurtosis-0.59372577
Mean48192.948
Median Absolute Deviation (MAD)3948
Skewness0.096660214
Sum7469907
Variance37281450
MonotonicityNot monotonic
2024-04-21T03:35:56.573653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
46157 1
 
0.6%
54372 1
 
0.6%
57469 1
 
0.6%
57588 1
 
0.6%
56061 1
 
0.6%
55286 1
 
0.6%
51983 1
 
0.6%
49958 1
 
0.6%
60871 1
 
0.6%
55342 1
 
0.6%
Other values (145) 145
93.5%
ValueCountFrequency (%)
33720 1
0.6%
34004 1
0.6%
35575 1
0.6%
36103 1
0.6%
36270 1
0.6%
36512 1
0.6%
37287 1
0.6%
37338 1
0.6%
38386 1
0.6%
38949 1
0.6%
ValueCountFrequency (%)
60871 1
0.6%
60504 1
0.6%
60280 1
0.6%
59623 1
0.6%
59387 1
0.6%
59006 1
0.6%
58153 1
0.6%
57938 1
0.6%
57805 1
0.6%
57588 1
0.6%

신청자(명)
Real number (ℝ)

HIGH CORRELATION 

Distinct154
Distinct (%)99.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean17105.587
Minimum612
Maximum61951
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2024-04-21T03:35:56.702585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum612
5-th percentile956.8
Q16303
median14359
Q323627.5
95-th percentile47464
Maximum61951
Range61339
Interquartile range (IQR)17324.5

Descriptive statistics

Standard deviation14314.974
Coefficient of variation (CV)0.83685953
Kurtosis0.54090319
Mean17105.587
Median Absolute Deviation (MAD)8415
Skewness1.0572893
Sum2651366
Variance2.0491847 × 108
MonotonicityNot monotonic
2024-04-21T03:35:56.809933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2037 2
 
1.3%
54124 1
 
0.6%
15594 1
 
0.6%
27112 1
 
0.6%
18639 1
 
0.6%
21679 1
 
0.6%
17725 1
 
0.6%
18730 1
 
0.6%
20383 1
 
0.6%
15892 1
 
0.6%
Other values (144) 144
92.9%
ValueCountFrequency (%)
612 1
0.6%
672 1
0.6%
721 1
0.6%
767 1
0.6%
843 1
0.6%
847 1
0.6%
913 1
0.6%
940 1
0.6%
964 1
0.6%
1126 1
0.6%
ValueCountFrequency (%)
61951 1
0.6%
58127 1
0.6%
54813 1
0.6%
54124 1
0.6%
52618 1
0.6%
49915 1
0.6%
49786 1
0.6%
47758 1
0.6%
47338 1
0.6%
46954 1
0.6%

Interactions

2024-04-21T03:35:55.372999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T03:35:54.803383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T03:35:55.175341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T03:35:55.437723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T03:35:54.913550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T03:35:55.240294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T03:35:55.505747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T03:35:55.109076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T03:35:55.304489image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-21T03:35:56.896179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기준년도반기구분시군명지급자(명)1인평균지급금액(원)신청자(명)
기준년도1.0000.2420.0000.0000.2840.000
반기구분0.2421.0000.0000.3500.9840.000
시군명0.0000.0001.0000.8980.7810.893
지급자(명)0.0000.3500.8981.0000.1910.997
1인평균지급금액(원)0.2840.9840.7810.1911.0000.000
신청자(명)0.0000.0000.8930.9970.0001.000
2024-04-21T03:35:56.978168image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군명기준년도반기구분
시군명1.0000.0000.000
기준년도0.0001.0000.393
반기구분0.0000.3931.000
2024-04-21T03:35:57.204159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
지급자(명)1인평균지급금액(원)신청자(명)기준년도반기구분시군명
지급자(명)1.0000.3130.9990.0000.2610.548
1인평균지급금액(원)0.3131.0000.3040.1780.8670.363
신청자(명)0.9990.3041.0000.0000.0000.538
기준년도0.0000.1780.0001.0000.3930.000
반기구분0.2610.8670.0000.3931.0000.000
시군명0.5480.3630.5380.0000.0001.000

Missing values

2024-04-21T03:35:55.596957image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-21T03:35:55.688719image/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

기준년도반기구분시군명지급자(명)1인평균지급금액(원)신청자(명)
02023상반기수원시474604615754124
12023상반기연천군80442695940
22023상반기고양시358144270241428
32023상반기성남시379724500342909
42023상반기부천시274454509031339
52023상반기화성시157994680720111
62023상반기안산시230574319926842
72023상반기남양주시290404544433131
82023상반기안양시251254696728385
92023상반기평택시190854577421749
기준년도반기구분시군명지급자(명)1인평균지급금액(원)신청자(명)
1452021상반기구리시6083445866771
1462021상반기안성시4337446574844
1472021상반기포천시2658481752966
1482021상반기의왕시5801486916300
1492021상반기양평군1204340041507
1502021상반기여주시2029409202271
1512021상반기동두천시1453337201808
1522021상반기가평군44038949612
1532021상반기과천시1695355751973
1542021상반기용인시339644419537852