Overview

Dataset statistics

Number of variables7
Number of observations30
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.9 KiB
Average record size in memory65.4 B

Variable types

Numeric5
DateTime1
Text1

Dataset

Description샘플 데이터
Author더아이엠씨
URLhttps://bigdata-region.kr/#/dataset/a131598b-2d55-4fb4-a600-226e7a65243a

Alerts

수집년월 has constant value ""Constant
분석인덱스 is highly overall correlated with 단어빈도 and 2 other fieldsHigh correlation
단어빈도 is highly overall correlated with 분석인덱스 and 2 other fieldsHigh correlation
연결정도중심성 is highly overall correlated with 분석인덱스 and 2 other fieldsHigh correlation
매개중심성 is highly overall correlated with 분석인덱스 and 2 other fieldsHigh correlation
분석인덱스 has unique valuesUnique
키워드명 has unique valuesUnique
매개중심성 has 1 (3.3%) zerosZeros

Reproduction

Analysis started2023-12-10 14:15:23.345232
Analysis finished2023-12-10 14:15:28.038042
Duration4.69 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

분석인덱스
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean15.5
Minimum1
Maximum30
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T23:15:28.148693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.45
Q18.25
median15.5
Q322.75
95-th percentile28.55
Maximum30
Range29
Interquartile range (IQR)14.5

Descriptive statistics

Standard deviation8.8034084
Coefficient of variation (CV)0.56796183
Kurtosis-1.2
Mean15.5
Median Absolute Deviation (MAD)7.5
Skewness0
Sum465
Variance77.5
MonotonicityStrictly increasing
2023-12-10T23:15:28.461470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
1 1
 
3.3%
17 1
 
3.3%
30 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%
Other values (20) 20
66.7%
ValueCountFrequency (%)
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%
10 1
3.3%
ValueCountFrequency (%)
30 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%
21 1
3.3%

수집년월
Date

CONSTANT 

Distinct1
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
Minimum2010-01-01 00:00:00
Maximum2010-01-01 00:00:00
2023-12-10T23:15:28.677566image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:15:28.897550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

키워드명
Text

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
2023-12-10T23:15:29.146710image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length2
Mean length2.3333333
Min length1

Characters and Unicode

Total characters70
Distinct characters49
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique30 ?
Unique (%)100.0%

Sample

1st row경기도
2nd row지원
3rd row창업
4th row프랜차이즈
5th row소상공인
ValueCountFrequency (%)
경기도 1
 
3.3%
지원 1
 
3.3%
평택 1
 
3.3%
업체 1
 
3.3%
직업 1
 
3.3%
시장 1
 
3.3%
기업 1
 
3.3%
수원 1
 
3.3%
보증 1
 
3.3%
거주 1
 
3.3%
Other values (20) 20
66.7%
2023-12-10T23:15:30.021025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
업 9
 
12.9%
기 4
 
5.7%
자 3
 
4.3%
경 2
 
2.9%
소 2
 
2.9%
보 2
 
2.9%
사 2
 
2.9%
영 2
 
2.9%
상 2
 
2.9%
공 2
 
2.9%
Other values (39) 40
57.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 70
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
업 9
 
12.9%
기 4
 
5.7%
자 3
 
4.3%
경 2
 
2.9%
소 2
 
2.9%
보 2
 
2.9%
사 2
 
2.9%
영 2
 
2.9%
상 2
 
2.9%
공 2
 
2.9%
Other values (39) 40
57.1%

Most occurring scripts

ValueCountFrequency (%)
Hangul 70
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
업 9
 
12.9%
기 4
 
5.7%
자 3
 
4.3%
경 2
 
2.9%
소 2
 
2.9%
보 2
 
2.9%
사 2
 
2.9%
영 2
 
2.9%
상 2
 
2.9%
공 2
 
2.9%
Other values (39) 40
57.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 70
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
업 9
 
12.9%
기 4
 
5.7%
자 3
 
4.3%
경 2
 
2.9%
소 2
 
2.9%
보 2
 
2.9%
사 2
 
2.9%
영 2
 
2.9%
상 2
 
2.9%
공 2
 
2.9%
Other values (39) 40
57.1%

단어빈도
Real number (ℝ)

HIGH CORRELATION 

Distinct25
Distinct (%)83.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean101.03333
Minimum36
Maximum601
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T23:15:30.441681image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum36
5-th percentile39.25
Q144
median52
Q396
95-th percentile239.15
Maximum601
Range565
Interquartile range (IQR)52

Descriptive statistics

Standard deviation114.30947
Coefficient of variation (CV)1.1314035
Kurtosis12.516858
Mean101.03333
Median Absolute Deviation (MAD)12.5
Skewness3.2384667
Sum3031
Variance13066.654
MonotonicityDecreasing
2023-12-10T23:15:30.863524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
44 3
 
10.0%
42 2
 
6.7%
43 2
 
6.7%
50 2
 
6.7%
601 1
 
3.3%
245 1
 
3.3%
36 1
 
3.3%
37 1
 
3.3%
46 1
 
3.3%
48 1
 
3.3%
Other values (15) 15
50.0%
ValueCountFrequency (%)
36 1
 
3.3%
37 1
 
3.3%
42 2
6.7%
43 2
6.7%
44 3
10.0%
46 1
 
3.3%
48 1
 
3.3%
49 1
 
3.3%
50 2
6.7%
51 1
 
3.3%
ValueCountFrequency (%)
601 1
3.3%
245 1
3.3%
232 1
3.3%
227 1
3.3%
211 1
3.3%
179 1
3.3%
104 1
3.3%
102 1
3.3%
78 1
3.3%
68 1
3.3%

단어중요도
Real number (ℝ)

Distinct27
Distinct (%)90.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.027476667
Minimum0.0208
Maximum0.0452
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T23:15:31.292908image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.0208
5-th percentile0.0209
Q10.023
median0.02555
Q30.031425
95-th percentile0.03734
Maximum0.0452
Range0.0244
Interquartile range (IQR)0.008425

Descriptive statistics

Standard deviation0.0062350336
Coefficient of variation (CV)0.22692103
Kurtosis0.65724068
Mean0.027476667
Median Absolute Deviation (MAD)0.0036
Skewness1.1220029
Sum0.8243
Variance3.8875644 × 10-5
MonotonicityNot monotonic
2023-12-10T23:15:31.627414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
0.0236 2
 
6.7%
0.0303 2
 
6.7%
0.0209 2
 
6.7%
0.0228 1
 
3.3%
0.0334 1
 
3.3%
0.0364 1
 
3.3%
0.0217 1
 
3.3%
0.0241 1
 
3.3%
0.0214 1
 
3.3%
0.0222 1
 
3.3%
Other values (17) 17
56.7%
ValueCountFrequency (%)
0.0208 1
3.3%
0.0209 2
6.7%
0.0214 1
3.3%
0.0217 1
3.3%
0.0222 1
3.3%
0.0228 1
3.3%
0.0229 1
3.3%
0.0233 1
3.3%
0.0236 2
6.7%
0.0241 1
3.3%
ValueCountFrequency (%)
0.0452 1
3.3%
0.0377 1
3.3%
0.0369 1
3.3%
0.0364 1
3.3%
0.0353 1
3.3%
0.0342 1
3.3%
0.0334 1
3.3%
0.0318 1
3.3%
0.0303 2
6.7%
0.0266 1
3.3%

연결정도중심성
Real number (ℝ)

HIGH CORRELATION 

Distinct20
Distinct (%)66.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.04012
Minimum0.002
Maximum0.1677
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T23:15:32.001468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.002
5-th percentile0.008045
Q10.0207
median0.0279
Q30.040875
95-th percentile0.129455
Maximum0.1677
Range0.1657
Interquartile range (IQR)0.020175

Descriptive statistics

Standard deviation0.038480442
Coefficient of variation (CV)0.95913365
Kurtosis4.4109334
Mean0.04012
Median Absolute Deviation (MAD)0.0114
Skewness2.1564782
Sum1.2036
Variance0.0014807444
MonotonicityNot monotonic
2023-12-10T23:15:32.307446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
0.0227 3
 
10.0%
0.0207 3
 
10.0%
0.031 2
 
6.7%
0.0124 2
 
6.7%
0.0414 2
 
6.7%
0.0372 2
 
6.7%
0.0393 2
 
6.7%
0.0248 2
 
6.7%
0.0103 1
 
3.3%
0.0165 1
 
3.3%
Other values (10) 10
33.3%
ValueCountFrequency (%)
0.002 1
 
3.3%
0.0062 1
 
3.3%
0.0103 1
 
3.3%
0.0124 2
6.7%
0.0165 1
 
3.3%
0.0186 1
 
3.3%
0.0207 3
10.0%
0.0227 3
10.0%
0.0248 2
6.7%
0.031 2
6.7%
ValueCountFrequency (%)
0.1677 1
3.3%
0.1304 1
3.3%
0.1283 1
3.3%
0.0724 1
3.3%
0.0703 1
3.3%
0.0434 1
3.3%
0.0414 2
6.7%
0.0393 2
6.7%
0.0372 2
6.7%
0.0351 1
3.3%

매개중심성
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct29
Distinct (%)96.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.046796667
Minimum0
Maximum0.2605
Zeros1
Zeros (%)3.3%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T23:15:32.689977image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.00227
Q10.0131
median0.0232
Q30.03765
95-th percentile0.24042
Maximum0.2605
Range0.2605
Interquartile range (IQR)0.02455

Descriptive statistics

Standard deviation0.071261918
Coefficient of variation (CV)1.522799
Kurtosis4.7628937
Mean0.046796667
Median Absolute Deviation (MAD)0.01235
Skewness2.4093897
Sum1.4039
Variance0.005078261
MonotonicityNot monotonic
2023-12-10T23:15:33.033022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
0.0131 2
 
6.7%
0.2605 1
 
3.3%
0.035 1
 
3.3%
0.0043 1
 
3.3%
0.0085 1
 
3.3%
0.0266 1
 
3.3%
0.0037 1
 
3.3%
0.036 1
 
3.3%
0.0263 1
 
3.3%
0.0011 1
 
3.3%
Other values (19) 19
63.3%
ValueCountFrequency (%)
0.0 1
3.3%
0.0011 1
3.3%
0.0037 1
3.3%
0.0041 1
3.3%
0.0043 1
3.3%
0.0085 1
3.3%
0.0113 1
3.3%
0.0131 2
6.7%
0.0134 1
3.3%
0.0135 1
3.3%
ValueCountFrequency (%)
0.2605 1
3.3%
0.2451 1
3.3%
0.2347 1
3.3%
0.1075 1
3.3%
0.0705 1
3.3%
0.0427 1
3.3%
0.0383 1
3.3%
0.0382 1
3.3%
0.036 1
3.3%
0.035 1
3.3%

Interactions

2023-12-10T23:15:27.065580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:15:23.934621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:15:24.960515image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:15:25.724827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:15:26.371853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:15:27.164719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:15:24.218524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:15:25.106501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:15:25.873888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:15:26.541160image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:15:27.278093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:15:24.464126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:15:25.253121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:15:26.018900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:15:26.689247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:15:27.400009image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:15:24.628026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:15:25.404543image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:15:26.135684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:15:26.814984image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:15:27.538664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:15:24.792223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:15:25.567532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:15:26.257566image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:15:26.939280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T23:15:33.192272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
분석인덱스키워드명단어빈도단어중요도연결정도중심성매개중심성
분석인덱스1.0001.0000.8570.1850.4630.615
키워드명1.0001.0001.0001.0001.0001.000
단어빈도0.8571.0001.0000.0000.7870.930
단어중요도0.1851.0000.0001.0000.0000.000
연결정도중심성0.4631.0000.7870.0001.0000.832
매개중심성0.6151.0000.9300.0000.8321.000
2023-12-10T23:15:33.749464image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
분석인덱스단어빈도단어중요도연결정도중심성매개중심성
분석인덱스1.000-0.999-0.260-0.779-0.657
단어빈도-0.9991.0000.2680.7810.661
단어중요도-0.2600.2681.0000.2410.044
연결정도중심성-0.7790.7810.2411.0000.926
매개중심성-0.6570.6610.0440.9261.000

Missing values

2023-12-10T23:15:27.731938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T23:15:27.953935image/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

분석인덱스수집년월키워드명단어빈도단어중요도연결정도중심성매개중심성
012010-01경기도6010.02360.16770.2605
122010-01지원2450.03690.07240.0705
232010-01창업2320.03770.13040.2451
342010-01프랜차이즈2270.02470.12830.2347
452010-01소상공인2110.02550.04340.0277
562010-01자영업1790.02290.07030.1075
672010-01중소기업1040.03030.02270.0113
782010-01자금1020.02620.04140.0383
892010-01사업780.02560.03720.034
9102010-01경기680.0260.03930.0219
분석인덱스수집년월키워드명단어빈도단어중요도연결정도중심성매개중심성
20212010-01운영460.02420.01860.0134
21222010-01거주440.02080.0020.0
22232010-01보증440.02220.02070.0131
23242010-01수원440.02360.00620.0011
24252010-01기업430.02140.02270.0263
25262010-01시장430.02410.03720.036
26272010-01직업420.02170.01240.0037
27282010-01업체420.02090.02480.0266
28292010-01평택370.03640.01650.0085
29302010-01사업자360.03340.01240.0043