Overview

Dataset statistics

Number of variables4
Number of observations30
Missing cells1
Missing cells (%)0.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.2 KiB
Average record size in memory39.4 B

Variable types

Numeric3
Text1

Dataset

Description샘플 데이터
Author경기도경제과학진흥원
URLhttps://bigdata-region.kr/#/dataset/e70f4772-4c10-4d38-a308-1159f0eccd63

Alerts

우편번호 has 1 (3.3%) missing valuesMissing
분석인덱스 has unique valuesUnique
분석인덱스 has 1 (3.3%) zerosZeros

Reproduction

Analysis started2023-12-10 13:55:26.607520
Analysis finished2023-12-10 13:55:29.157208
Duration2.55 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

분석인덱스
Real number (ℝ)

UNIQUE  ZEROS 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean14.5
Minimum0
Maximum29
Zeros1
Zeros (%)3.3%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T22:55:29.282938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1.45
Q17.25
median14.5
Q321.75
95-th percentile27.55
Maximum29
Range29
Interquartile range (IQR)14.5

Descriptive statistics

Standard deviation8.8034084
Coefficient of variation (CV)0.60713162
Kurtosis-1.2
Mean14.5
Median Absolute Deviation (MAD)7.5
Skewness0
Sum435
Variance77.5
MonotonicityStrictly increasing
2023-12-10T22:55:29.622688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
0 1
 
3.3%
16 1
 
3.3%
29 1
 
3.3%
28 1
 
3.3%
27 1
 
3.3%
26 1
 
3.3%
25 1
 
3.3%
24 1
 
3.3%
23 1
 
3.3%
22 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
0 1
3.3%
1 1
3.3%
2 1
3.3%
3 1
3.3%
4 1
3.3%
5 1
3.3%
6 1
3.3%
7 1
3.3%
8 1
3.3%
9 1
3.3%
ValueCountFrequency (%)
29 1
3.3%
28 1
3.3%
27 1
3.3%
26 1
3.3%
25 1
3.3%
24 1
3.3%
23 1
3.3%
22 1
3.3%
21 1
3.3%
20 1
3.3%

우편번호
Real number (ℝ)

MISSING 

Distinct27
Distinct (%)93.1%
Missing1
Missing (%)3.3%
Infinite0
Infinite (%)0.0%
Mean10068.724
Minimum3051
Maximum18583
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T22:55:29.886237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3051
5-th percentile3156
Q14513
median10257
Q314057
95-th percentile18448.8
Maximum18583
Range15532
Interquartile range (IQR)9544

Descriptive statistics

Standard deviation5278.1779
Coefficient of variation (CV)0.52421517
Kurtosis-1.3104768
Mean10068.724
Median Absolute Deviation (MAD)4366
Skewness0.20575206
Sum291993
Variance27859162
MonotonicityNot monotonic
2023-12-10T22:55:30.149278image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
10881 3
 
10.0%
16643 1
 
3.3%
14057 1
 
3.3%
8588 1
 
3.3%
4376 1
 
3.3%
11623 1
 
3.3%
14623 1
 
3.3%
18578 1
 
3.3%
6103 1
 
3.3%
13605 1
 
3.3%
Other values (17) 17
56.7%
ValueCountFrequency (%)
3051 1
3.3%
3134 1
3.3%
3189 1
3.3%
3909 1
3.3%
3997 1
3.3%
4074 1
3.3%
4376 1
3.3%
4513 1
3.3%
6103 1
3.3%
6633 1
3.3%
ValueCountFrequency (%)
18583 1
3.3%
18578 1
3.3%
18255 1
3.3%
16898 1
3.3%
16827 1
3.3%
16643 1
3.3%
14623 1
3.3%
14057 1
3.3%
14056 1
3.3%
13605 1
3.3%

범주명
Text

Distinct15
Distinct (%)50.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
2023-12-10T22:55:30.454801image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length14
Mean length12.8
Min length8

Characters and Unicode

Total characters384
Distinct characters106
Distinct categories4 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9 ?
Unique (%)30.0%

Sample

1st row기기;기계;장비
2nd row의료;보건;복지;제약;동물
3rd row연구;조사;분석;컨설팅;R&D
4th row웹;모바일프로그래밍
5th row온라인 포털; 호스팅
ValueCountFrequency (%)
웹;모바일프로그래밍 6
18.8%
언론;방송;연예;공연 4
12.5%
판매;유통;무역;도소매;운송;물류 4
12.5%
마케팅;광고;홍보;전시;출판;인쇄 3
9.4%
기기;기계;장비 2
 
6.2%
의료;보건;복지;제약;동물 2
 
6.2%
교육;유학;어학 1
 
3.1%
솔루션;si;시스템;it컨설팅 1
 
3.1%
임업;가구;목재;제지 1
 
3.1%
생활가전;용품;소비재;사무 1
 
3.1%
Other values (7) 7
21.9%
2023-12-10T22:55:31.027674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
; 87
 
22.7%
연 9
 
2.3%
송 8
 
2.1%
매 8
 
2.1%
판 7
 
1.8%
웹 6
 
1.6%
팅 6
 
1.6%
기 6
 
1.6%
유 6
 
1.6%
물 6
 
1.6%
Other values (96) 235
61.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 286
74.5%
Other Punctuation 88
 
22.9%
Uppercase Letter 8
 
2.1%
Space Separator 2
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
연 9
 
3.1%
송 8
 
2.8%
매 8
 
2.8%
판 7
 
2.4%
웹 6
 
2.1%
팅 6
 
2.1%
기 6
 
2.1%
유 6
 
2.1%
물 6
 
2.1%
밍 6
 
2.1%
Other values (88) 218
76.2%
Uppercase Letter
ValueCountFrequency (%)
I 3
37.5%
T 2
25.0%
S 1
 
12.5%
R 1
 
12.5%
D 1
 
12.5%
Other Punctuation
ValueCountFrequency (%)
; 87
98.9%
& 1
 
1.1%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 286
74.5%
Common 90
 
23.4%
Latin 8
 
2.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
연 9
 
3.1%
송 8
 
2.8%
매 8
 
2.8%
판 7
 
2.4%
웹 6
 
2.1%
팅 6
 
2.1%
기 6
 
2.1%
유 6
 
2.1%
물 6
 
2.1%
밍 6
 
2.1%
Other values (88) 218
76.2%
Latin
ValueCountFrequency (%)
I 3
37.5%
T 2
25.0%
S 1
 
12.5%
R 1
 
12.5%
D 1
 
12.5%
Common
ValueCountFrequency (%)
; 87
96.7%
2
 
2.2%
& 1
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 286
74.5%
ASCII 98
 
25.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
; 87
88.8%
I 3
 
3.1%
2
 
2.0%
T 2
 
2.0%
S 1
 
1.0%
R 1
 
1.0%
& 1
 
1.0%
D 1
 
1.0%
Hangul
ValueCountFrequency (%)
연 9
 
3.1%
송 8
 
2.8%
매 8
 
2.8%
판 7
 
2.4%
웹 6
 
2.1%
팅 6
 
2.1%
기 6
 
2.1%
유 6
 
2.1%
물 6
 
2.1%
밍 6
 
2.1%
Other values (88) 218
76.2%

복지지수
Real number (ℝ)

Distinct13
Distinct (%)43.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.3333333
Minimum1
Maximum19
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T22:55:31.254822image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13
median5.5
Q38.75
95-th percentile13
Maximum19
Range18
Interquartile range (IQR)5.75

Descriptive statistics

Standard deviation4.2938074
Coefficient of variation (CV)0.67796958
Kurtosis1.0347514
Mean6.3333333
Median Absolute Deviation (MAD)3
Skewness0.93070299
Sum190
Variance18.436782
MonotonicityNot monotonic
2023-12-10T22:55:31.841106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
5 4
13.3%
2 4
13.3%
3 3
10.0%
7 3
10.0%
1 3
10.0%
10 3
10.0%
8 3
10.0%
13 2
6.7%
6 1
 
3.3%
9 1
 
3.3%
Other values (3) 3
10.0%
ValueCountFrequency (%)
1 3
10.0%
2 4
13.3%
3 3
10.0%
4 1
 
3.3%
5 4
13.3%
6 1
 
3.3%
7 3
10.0%
8 3
10.0%
9 1
 
3.3%
10 3
10.0%
ValueCountFrequency (%)
19 1
 
3.3%
13 2
6.7%
11 1
 
3.3%
10 3
10.0%
9 1
 
3.3%
8 3
10.0%
7 3
10.0%
6 1
 
3.3%
5 4
13.3%
4 1
 
3.3%

Interactions

2023-12-10T22:55:28.353308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:55:27.013633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:55:27.834925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:55:28.523151image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:55:27.271005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:55:28.011348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:55:28.736657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:55:27.535484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:55:28.222501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T22:55:31.990567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
분석인덱스우편번호범주명복지지수
분석인덱스1.0000.6630.4760.643
우편번호0.6631.0000.3360.601
범주명0.4760.3361.0000.628
복지지수0.6430.6010.6281.000
2023-12-10T22:55:32.189970image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
분석인덱스우편번호복지지수
분석인덱스1.0000.093-0.038
우편번호0.0931.0000.134
복지지수-0.0380.1341.000

Missing values

2023-12-10T22:55:28.943388image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T22:55:29.080162image/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

분석인덱스우편번호범주명복지지수
0016643기기;기계;장비3
1116827의료;보건;복지;제약;동물13
223189연구;조사;분석;컨설팅;R&D6
333909웹;모바일프로그래밍7
443051온라인 포털; 호스팅7
5516898판매;유통;무역;도소매;운송;물류3
664513석유;화학;에너지;환경9
773134교육;유학;어학5
8810881마케팅;광고;홍보;전시;출판;인쇄1
9918583기기;기계;장비5
분석인덱스우편번호범주명복지지수
20206633웹;모바일프로그래밍8
21217976언론;방송;연예;공연1
222213605의료;보건;복지;제약;동물10
232310881마케팅;광고;홍보;전시;출판;인쇄1
24246103마케팅;광고;홍보;전시;출판;인쇄3
252518578임업;가구;목재;제지4
262614623솔루션;SI;시스템;IT컨설팅11
272711623IT하드웨어;장비2
28284376판매;유통;무역;도소매;운송;물류7
29298588언론;방송;연예;공연10