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/17d039bb-8711-4042-987d-0cbcedbd3070

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
단어빈도 has unique valuesUnique

Reproduction

Analysis started2023-12-10 13:43:57.954194
Analysis finished2023-12-10 13:44:02.929841
Duration4.98 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
2023-12-10T22:44:03.102688image/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
2023-12-10T22:44:03.307130image/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
2023-12-10T22:44:03.507881image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:44:03.778994image/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
2023-12-10T22:44:04.086620image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length2
Mean length2.4
Min length1

Characters and Unicode

Total characters72
Distinct characters50
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 row미용업
2nd row독서실
3rd row머리
4th row세탁소
5th row공부
ValueCountFrequency (%)
미용업 1
 
3.3%
독서실 1
 
3.3%
운영 1
 
3.3%
메이크업 1
 
3.3%
시설 1
 
3.3%
헤어스타일 1
 
3.3%
가격 1
 
3.3%
여자 1
 
3.3%
아이 1
 
3.3%
정보 1
 
3.3%
Other values (20) 20
66.7%
2023-12-10T22:44:04.900020image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
리 3
 
4.2%
용 3
 
4.2%
부 3
 
4.2%
미 2
 
2.8%
피 2
 
2.8%
이 2
 
2.8%
아 2
 
2.8%
일 2
 
2.8%
타 2
 
2.8%
스 2
 
2.8%
Other values (40) 49
68.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 72
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
리 3
 
4.2%
용 3
 
4.2%
부 3
 
4.2%
미 2
 
2.8%
피 2
 
2.8%
이 2
 
2.8%
아 2
 
2.8%
일 2
 
2.8%
타 2
 
2.8%
스 2
 
2.8%
Other values (40) 49
68.1%

Most occurring scripts

ValueCountFrequency (%)
Hangul 72
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
리 3
 
4.2%
용 3
 
4.2%
부 3
 
4.2%
미 2
 
2.8%
피 2
 
2.8%
이 2
 
2.8%
아 2
 
2.8%
일 2
 
2.8%
타 2
 
2.8%
스 2
 
2.8%
Other values (40) 49
68.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 72
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
리 3
 
4.2%
용 3
 
4.2%
부 3
 
4.2%
미 2
 
2.8%
피 2
 
2.8%
이 2
 
2.8%
아 2
 
2.8%
일 2
 
2.8%
타 2
 
2.8%
스 2
 
2.8%
Other values (40) 49
68.1%

단어빈도
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1224.8667
Minimum377
Maximum10112
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T22:44:05.151443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum377
5-th percentile391.75
Q1510.5
median594
Q3789.5
95-th percentile3997.3
Maximum10112
Range9735
Interquartile range (IQR)279

Descriptive statistics

Standard deviation1920.2619
Coefficient of variation (CV)1.5677314
Kurtosis16.519948
Mean1224.8667
Median Absolute Deviation (MAD)144
Skewness3.8573026
Sum36746
Variance3687405.8
MonotonicityStrictly decreasing
2023-12-10T22:44:05.472721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
10112 1
 
3.3%
554 1
 
3.3%
377 1
 
3.3%
385 1
 
3.3%
400 1
 
3.3%
408 1
 
3.3%
426 1
 
3.3%
438 1
 
3.3%
462 1
 
3.3%
510 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
377 1
3.3%
385 1
3.3%
400 1
3.3%
408 1
3.3%
426 1
3.3%
438 1
3.3%
462 1
3.3%
510 1
3.3%
512 1
3.3%
526 1
3.3%
ValueCountFrequency (%)
10112 1
3.3%
4135 1
3.3%
3829 1
3.3%
2613 1
3.3%
1220 1
3.3%
1162 1
3.3%
936 1
3.3%
800 1
3.3%
758 1
3.3%
712 1
3.3%

단어중요도
Real number (ℝ)

Distinct29
Distinct (%)96.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.032093333
Minimum0.0229
Maximum0.0457
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T22:44:05.710747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.0229
5-th percentile0.024115
Q10.027225
median0.0308
Q30.036125
95-th percentile0.044815
Maximum0.0457
Range0.0228
Interquartile range (IQR)0.0089

Descriptive statistics

Standard deviation0.0065752374
Coefficient of variation (CV)0.20487861
Kurtosis-0.4954991
Mean0.032093333
Median Absolute Deviation (MAD)0.0043
Skewness0.64984389
Sum0.9628
Variance4.3233747 × 10-5
MonotonicityNot monotonic
2023-12-10T22:44:06.280145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
0.0304 2
 
6.7%
0.0457 1
 
3.3%
0.027 1
 
3.3%
0.0229 1
 
3.3%
0.0312 1
 
3.3%
0.0245 1
 
3.3%
0.0454 1
 
3.3%
0.0238 1
 
3.3%
0.0397 1
 
3.3%
0.028 1
 
3.3%
Other values (19) 19
63.3%
ValueCountFrequency (%)
0.0229 1
3.3%
0.0238 1
3.3%
0.0245 1
3.3%
0.0248 1
3.3%
0.0252 1
3.3%
0.0253 1
3.3%
0.027 1
3.3%
0.0271 1
3.3%
0.0276 1
3.3%
0.0278 1
3.3%
ValueCountFrequency (%)
0.0457 1
3.3%
0.0454 1
3.3%
0.0441 1
3.3%
0.0412 1
3.3%
0.0397 1
3.3%
0.0392 1
3.3%
0.0368 1
3.3%
0.0363 1
3.3%
0.0356 1
3.3%
0.0343 1
3.3%

연결정도중심성
Real number (ℝ)

HIGH CORRELATION 

Distinct25
Distinct (%)83.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.06674
Minimum0.0229
Maximum0.3193
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T22:44:06.554935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.0229
5-th percentile0.02588
Q10.037725
median0.05135
Q30.0659
95-th percentile0.152435
Maximum0.3193
Range0.2964
Interquartile range (IQR)0.028175

Descriptive statistics

Standard deviation0.057930551
Coefficient of variation (CV)0.86800345
Kurtosis12.612644
Mean0.06674
Median Absolute Deviation (MAD)0.01455
Skewness3.2546054
Sum2.0022
Variance0.0033559487
MonotonicityNot monotonic
2023-12-10T22:44:06.823069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
0.1002 2
 
6.7%
0.0309 2
 
6.7%
0.065 2
 
6.7%
0.0538 2
 
6.7%
0.0408 2
 
6.7%
0.3193 1
 
3.3%
0.0446 1
 
3.3%
0.047 1
 
3.3%
0.0285 1
 
3.3%
0.0396 1
 
3.3%
Other values (15) 15
50.0%
ValueCountFrequency (%)
0.0229 1
3.3%
0.0248 1
3.3%
0.0272 1
3.3%
0.0285 1
3.3%
0.0309 2
6.7%
0.0365 1
3.3%
0.0371 1
3.3%
0.0396 1
3.3%
0.0408 2
6.7%
0.0439 1
3.3%
ValueCountFrequency (%)
0.3193 1
3.3%
0.1739 1
3.3%
0.1262 1
3.3%
0.1002 2
6.7%
0.0941 1
3.3%
0.0699 1
3.3%
0.0662 1
3.3%
0.065 2
6.7%
0.0588 1
3.3%
0.0563 1
3.3%

매개중심성
Real number (ℝ)

HIGH CORRELATION 

Distinct28
Distinct (%)93.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.028493333
Minimum0.0019
Maximum0.2874
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T22:44:07.053102image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.0019
5-th percentile0.004445
Q10.006225
median0.01095
Q30.024875
95-th percentile0.09643
Maximum0.2874
Range0.2855
Interquartile range (IQR)0.01865

Descriptive statistics

Standard deviation0.054149741
Coefficient of variation (CV)1.9004355
Kurtosis19.154689
Mean0.028493333
Median Absolute Deviation (MAD)0.00585
Skewness4.1715176
Sum0.8548
Variance0.0029321944
MonotonicityNot monotonic
2023-12-10T22:44:07.348306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
0.0069 2
 
6.7%
0.0097 2
 
6.7%
0.0242 1
 
3.3%
0.0063 1
 
3.3%
0.0059 1
 
3.3%
0.0152 1
 
3.3%
0.0019 1
 
3.3%
0.0062 1
 
3.3%
0.0099 1
 
3.3%
0.017 1
 
3.3%
Other values (18) 18
60.0%
ValueCountFrequency (%)
0.0019 1
3.3%
0.0044 1
3.3%
0.0045 1
3.3%
0.0053 1
3.3%
0.0057 1
3.3%
0.0058 1
3.3%
0.0059 1
3.3%
0.0062 1
3.3%
0.0063 1
3.3%
0.0069 2
6.7%
ValueCountFrequency (%)
0.2874 1
3.3%
0.1156 1
3.3%
0.073 1
3.3%
0.0372 1
3.3%
0.0344 1
3.3%
0.033 1
3.3%
0.0278 1
3.3%
0.0251 1
3.3%
0.0242 1
3.3%
0.0224 1
3.3%

Interactions

2023-12-10T22:44:01.712711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:43:58.279273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:43:59.010684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:43:59.914394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:44:00.999244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:44:01.872244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:43:58.453186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:43:59.168604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:44:00.247508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:44:01.138832image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:44:02.004064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:43:58.589772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:43:59.315353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:44:00.516414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:44:01.265518image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:44:02.143407image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:43:58.717269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:43:59.458972image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:44:00.718490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:44:01.410790image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:44:02.296225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:43:58.860962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:43:59.639977image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:44:00.860565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:44:01.569649image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T22:44:07.501563image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
분석인덱스키워드명단어빈도단어중요도연결정도중심성매개중심성
분석인덱스1.0001.0000.6240.0000.4590.379
키워드명1.0001.0001.0001.0001.0001.000
단어빈도0.6241.0001.0000.0000.9870.917
단어중요도0.0001.0000.0001.0000.5550.705
연결정도중심성0.4591.0000.9870.5551.0001.000
매개중심성0.3791.0000.9170.7051.0001.000
2023-12-10T22:44:07.742456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
분석인덱스단어빈도단어중요도연결정도중심성매개중심성
분석인덱스1.000-1.000-0.462-0.680-0.586
단어빈도-1.0001.0000.4620.6800.586
단어중요도-0.4620.4621.0000.4870.286
연결정도중심성-0.6800.6800.4871.0000.932
매개중심성-0.5860.5860.2860.9321.000

Missing values

2023-12-10T22:44:02.561585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T22:44:02.842044image/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
012010-01미용업101120.04570.31930.2874
122010-01독서실41350.03040.17390.1156
232010-01머리38290.03560.10020.0344
342010-01세탁소26130.03250.12620.073
452010-01공부12200.02780.03090.0057
562010-01헤어11620.03680.10020.033
672010-01피부관리실9360.03630.09410.0372
782010-01펌8000.04120.05630.0097
892010-01남자7580.04410.05510.012
9102010-01학원7120.02710.06990.0224
분석인덱스수집년월키워드명단어빈도단어중요도연결정도중심성매개중심성
20212010-01친구5260.02530.02290.0044
21222010-01정보5120.03180.05380.017
22232010-01아이5100.0280.04080.0099
23242010-01여자4620.03970.04080.0062
24252010-01가격4380.02380.03090.0069
25262010-01헤어스타일4260.04540.03650.0019
26272010-01시설4080.02450.04890.0152
27282010-01메이크업4000.03120.03960.0059
28292010-01운영3850.02290.02850.0063
29302010-01아파트3770.0270.0470.0097