Overview

Dataset statistics

Number of variables10
Number of observations762
Missing cells3810
Missing cells (%)50.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory66.4 KiB
Average record size in memory89.2 B

Variable types

Numeric3
Categorical1
Text1
Unsupported5

Dataset

Description학점은행제 기관 주소 연계 우편번호에 대한 데이터로 우편번호(시도), 우편번호(시군구), 지역코드 등의 항목을 제공합니다.
Author국가평생교육진흥원
URLhttps://www.data.go.kr/data/15042350/fileData.do

Alerts

우편번호(시도) is highly overall correlated with 지역코드High correlation
지역코드 is highly overall correlated with 우편번호(시도)High correlation
Unnamed: 5 has 762 (100.0%) missing valuesMissing
Unnamed: 6 has 762 (100.0%) missing valuesMissing
Unnamed: 7 has 762 (100.0%) missing valuesMissing
Unnamed: 8 has 762 (100.0%) missing valuesMissing
Unnamed: 9 has 762 (100.0%) missing valuesMissing
Unnamed: 5 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 6 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 7 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 8 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 9 is an unsupported type, check if it needs cleaning or further analysisUnsupported
우편번호(시군구) has 111 (14.6%) zerosZeros

Reproduction

Analysis started2023-12-12 07:27:02.750520
Analysis finished2023-12-12 07:27:04.133850
Duration1.38 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

우편번호(시도)
Real number (ℝ)

HIGH CORRELATION 

Distinct76
Distinct (%)10.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean36.48294
Minimum1
Maximum79
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.8 KiB
2023-12-12T16:27:04.223483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile4
Q118
median38
Q352
95-th percentile68
Maximum79
Range78
Interquartile range (IQR)34

Descriptive statistics

Standard deviation19.940393
Coefficient of variation (CV)0.54656762
Kurtosis-1.0167382
Mean36.48294
Median Absolute Deviation (MAD)16
Skewness-0.044440381
Sum27800
Variance397.61929
MonotonicityNot monotonic
2023-12-12T16:27:04.355663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
13 20
 
2.6%
44 19
 
2.5%
61 18
 
2.4%
42 18
 
2.4%
46 17
 
2.2%
36 17
 
2.2%
15 17
 
2.2%
41 16
 
2.1%
48 15
 
2.0%
54 15
 
2.0%
Other values (66) 590
77.4%
ValueCountFrequency (%)
1 10
1.3%
2 10
1.3%
3 10
1.3%
4 10
1.3%
5 10
1.3%
6 10
1.3%
7 10
1.3%
8 10
1.3%
10 11
1.4%
11 11
1.4%
ValueCountFrequency (%)
79 3
0.4%
78 1
 
0.1%
77 1
 
0.1%
76 6
0.8%
75 3
0.4%
74 3
0.4%
73 1
 
0.1%
71 7
0.9%
70 7
0.9%
69 4
0.5%

우편번호(시군구)
Real number (ℝ)

ZEROS 

Distinct10
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.0984252
Minimum0
Maximum9
Zeros111
Zeros (%)14.6%
Negative0
Negative (%)0.0%
Memory size6.8 KiB
2023-12-12T16:27:04.505153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median4
Q37
95-th percentile9
Maximum9
Range9
Interquartile range (IQR)6

Descriptive statistics

Standard deviation2.9157279
Coefficient of variation (CV)0.71142641
Kurtosis-1.2280796
Mean4.0984252
Median Absolute Deviation (MAD)3
Skewness0.12596663
Sum3123
Variance8.5014693
MonotonicityNot monotonic
2023-12-12T16:27:04.609785image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
0 111
14.6%
1 84
11.0%
5 82
10.8%
2 78
10.2%
6 77
10.1%
3 74
9.7%
7 72
9.4%
9 65
8.5%
4 63
8.3%
8 56
7.3%
ValueCountFrequency (%)
0 111
14.6%
1 84
11.0%
2 78
10.2%
3 74
9.7%
4 63
8.3%
5 82
10.8%
6 77
10.1%
7 72
9.4%
8 56
7.3%
9 65
8.5%
ValueCountFrequency (%)
9 65
8.5%
8 56
7.3%
7 72
9.4%
6 77
10.1%
5 82
10.8%
4 63
8.3%
3 74
9.7%
2 78
10.2%
1 84
11.0%
0 111
14.6%

우편번호체계자리수
Categorical

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size6.1 KiB
5
505 
6
257 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row5
2nd row5
3rd row5
4th row5
5th row5

Common Values

ValueCountFrequency (%)
5 505
66.3%
6 257
33.7%

Length

2023-12-12T16:27:04.738033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T16:27:04.834112image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
5 505
66.3%
6 257
33.7%

지역코드
Real number (ℝ)

HIGH CORRELATION 

Distinct17
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean34.813648
Minimum11
Maximum49
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.8 KiB
2023-12-12T16:27:04.930794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum11
5-th percentile11
Q123
median41
Q345
95-th percentile48
Maximum49
Range38
Interquartile range (IQR)22

Descriptive statistics

Standard deviation13.093194
Coefficient of variation (CV)0.37609369
Kurtosis-1.060711
Mean34.813648
Median Absolute Deviation (MAD)6
Skewness-0.72067733
Sum26528
Variance171.43172
MonotonicityNot monotonic
2023-12-12T16:27:05.342177image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
41 134
17.6%
11 105
13.8%
47 67
8.8%
48 56
7.3%
46 53
 
7.0%
21 52
 
6.8%
42 44
 
5.8%
44 43
 
5.6%
45 40
 
5.2%
43 35
 
4.6%
Other values (7) 133
17.5%
ValueCountFrequency (%)
11 105
13.8%
21 52
 
6.8%
22 29
 
3.8%
23 32
 
4.2%
24 21
 
2.8%
25 20
 
2.6%
26 17
 
2.2%
36 3
 
0.4%
41 134
17.6%
42 44
 
5.8%
ValueCountFrequency (%)
49 11
 
1.4%
48 56
7.3%
47 67
8.8%
46 53
 
7.0%
45 40
 
5.2%
44 43
 
5.6%
43 35
 
4.6%
42 44
 
5.8%
41 134
17.6%
36 3
 
0.4%

시군구명칭
Text

Distinct264
Distinct (%)34.6%
Missing0
Missing (%)0.0%
Memory size6.1 KiB
2023-12-12T16:27:05.678790image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length3
Mean length3.1784777
Min length2

Characters and Unicode

Total characters2422
Distinct characters142
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

Unique61 ?
Unique (%)8.0%

Sample

1st row해운대구
2nd row수영구
3rd row수영구
4th row남구
5th row남구
ValueCountFrequency (%)
동구 20
 
2.5%
남구 19
 
2.3%
서구 18
 
2.2%
중구 17
 
2.1%
북구 16
 
2.0%
창원시 14
 
1.7%
청주시 10
 
1.2%
인천 10
 
1.2%
성남시 10
 
1.2%
수원시 10
 
1.2%
Other values (236) 669
82.3%
2023-12-12T16:27:06.181862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
시 328
 
13.5%
구 315
 
13.0%
군 184
 
7.6%
주 78
 
3.2%
천 76
 
3.1%
산 64
 
2.6%
성 62
 
2.6%
동 59
 
2.4%
양 59
 
2.4%
남 56
 
2.3%
Other values (132) 1141
47.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2367
97.7%
Space Separator 55
 
2.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 328
 
13.9%
구 315
 
13.3%
군 184
 
7.8%
주 78
 
3.3%
천 76
 
3.2%
산 64
 
2.7%
성 62
 
2.6%
동 59
 
2.5%
양 59
 
2.5%
남 56
 
2.4%
Other values (131) 1086
45.9%
Space Separator
ValueCountFrequency (%)
55
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2367
97.7%
Common 55
 
2.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 328
 
13.9%
구 315
 
13.3%
군 184
 
7.8%
주 78
 
3.3%
천 76
 
3.2%
산 64
 
2.7%
성 62
 
2.6%
동 59
 
2.5%
양 59
 
2.5%
남 56
 
2.4%
Other values (131) 1086
45.9%
Common
ValueCountFrequency (%)
55
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2367
97.7%
ASCII 55
 
2.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
시 328
 
13.9%
구 315
 
13.3%
군 184
 
7.8%
주 78
 
3.3%
천 76
 
3.2%
산 64
 
2.7%
성 62
 
2.6%
동 59
 
2.5%
양 59
 
2.5%
남 56
 
2.4%
Other values (131) 1086
45.9%
ASCII
ValueCountFrequency (%)
55
100.0%

Unnamed: 5
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing762
Missing (%)100.0%
Memory size6.8 KiB

Unnamed: 6
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing762
Missing (%)100.0%
Memory size6.8 KiB

Unnamed: 7
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing762
Missing (%)100.0%
Memory size6.8 KiB

Unnamed: 8
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing762
Missing (%)100.0%
Memory size6.8 KiB

Unnamed: 9
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing762
Missing (%)100.0%
Memory size6.8 KiB

Interactions

2023-12-12T16:27:03.587399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:27:03.011845image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:27:03.306554image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:27:03.689927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:27:03.123669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:27:03.410253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:27:03.777352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:27:03.211103image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:27:03.492202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T16:27:06.314955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
우편번호(시도)우편번호(시군구)우편번호체계자리수지역코드
우편번호(시도)1.0000.0000.5920.799
우편번호(시군구)0.0001.0000.1830.000
우편번호체계자리수0.5920.1831.0000.076
지역코드0.7990.0000.0761.000
2023-12-12T16:27:06.428517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
우편번호(시도)우편번호(시군구)지역코드우편번호체계자리수
우편번호(시도)1.000-0.0250.5400.455
우편번호(시군구)-0.0251.0000.0040.139
지역코드0.5400.0041.0000.081
우편번호체계자리수0.4550.1390.0811.000

Missing values

2023-12-12T16:27:03.930903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T16:27:04.078350image/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

우편번호(시도)우편번호(시군구)우편번호체계자리수지역코드시군구명칭Unnamed: 5Unnamed: 6Unnamed: 7Unnamed: 8Unnamed: 9
0481521해운대구<NA><NA><NA><NA><NA>
1482521수영구<NA><NA><NA><NA><NA>
2483521수영구<NA><NA><NA><NA><NA>
3484521남구<NA><NA><NA><NA><NA>
4485521남구<NA><NA><NA><NA><NA>
5486521남구<NA><NA><NA><NA><NA>
6487521동구<NA><NA><NA><NA><NA>
7488521동구<NA><NA><NA><NA><NA>
8489521중구<NA><NA><NA><NA><NA>
9490521영도구<NA><NA><NA><NA><NA>
우편번호(시도)우편번호(시군구)우편번호체계자리수지역코드시군구명칭Unnamed: 5Unnamed: 6Unnamed: 7Unnamed: 8Unnamed: 9
752471521부산진구<NA><NA><NA><NA><NA>
753472521부산진구<NA><NA><NA><NA><NA>
754473521부산진구<NA><NA><NA><NA><NA>
755474521부산진구<NA><NA><NA><NA><NA>
756475521연제구<NA><NA><NA><NA><NA>
757476521연제구<NA><NA><NA><NA><NA>
758477521동래구<NA><NA><NA><NA><NA>
759478521동래구<NA><NA><NA><NA><NA>
760479521동래구<NA><NA><NA><NA><NA>
761480521해운대구<NA><NA><NA><NA><NA>