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/60706d8d-6cf1-4ecc-827c-27c72fd2e212

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
단어중요도 is highly overall correlated with 매개중심성High correlation
연결정도중심성 is highly overall correlated with 분석인덱스 and 2 other fieldsHigh correlation
매개중심성 is highly overall correlated with 분석인덱스 and 3 other fieldsHigh correlation
분석인덱스 has unique valuesUnique
키워드명 has unique valuesUnique

Reproduction

Analysis started2023-12-10 14:03:28.079105
Analysis finished2023-12-10 14:03:32.823849
Duration4.74 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
2023-12-10T23:03:32.920727image/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
2023-12-10T23:03:33.093143image/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
2023-12-10T23:03:33.251787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:03:33.443219image/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
2023-12-10T23:03:33.714479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.2
Min length1

Characters and Unicode

Total characters66
Distinct characters45
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 row고양
2nd row경기
3rd row경기도
4th row서울
5th row분양
ValueCountFrequency (%)
고양 1
 
3.3%
경기 1
 
3.3%
사랑 1
 
3.3%
주택 1
 
3.3%
용인 1
 
3.3%
사업 1
 
3.3%
도시 1
 
3.3%
문화 1
 
3.3%
시민 1
 
3.3%
인천 1
 
3.3%
Other values (20) 20
66.7%
2023-12-10T23:03:34.227744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
시 4
 
6.1%
도 4
 
6.1%
주 3
 
4.5%
양 3
 
4.5%
부 3
 
4.5%
정 2
 
3.0%
인 2
 
3.0%
수 2
 
3.0%
사 2
 
3.0%
남 2
 
3.0%
Other values (35) 39
59.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 66
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 4
 
6.1%
도 4
 
6.1%
주 3
 
4.5%
양 3
 
4.5%
부 3
 
4.5%
정 2
 
3.0%
인 2
 
3.0%
수 2
 
3.0%
사 2
 
3.0%
남 2
 
3.0%
Other values (35) 39
59.1%

Most occurring scripts

ValueCountFrequency (%)
Hangul 66
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 4
 
6.1%
도 4
 
6.1%
주 3
 
4.5%
양 3
 
4.5%
부 3
 
4.5%
정 2
 
3.0%
인 2
 
3.0%
수 2
 
3.0%
사 2
 
3.0%
남 2
 
3.0%
Other values (35) 39
59.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 66
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
시 4
 
6.1%
도 4
 
6.1%
주 3
 
4.5%
양 3
 
4.5%
부 3
 
4.5%
정 2
 
3.0%
인 2
 
3.0%
수 2
 
3.0%
사 2
 
3.0%
남 2
 
3.0%
Other values (35) 39
59.1%

단어빈도
Real number (ℝ)

HIGH CORRELATION 

Distinct28
Distinct (%)93.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean737.16667
Minimum270
Maximum7690
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T23:03:34.450613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum270
5-th percentile275.8
Q1333
median373
Q3466.75
95-th percentile1488.15
Maximum7690
Range7420
Interquartile range (IQR)133.75

Descriptive statistics

Standard deviation1353.0852
Coefficient of variation (CV)1.8355214
Kurtosis26.252003
Mean737.16667
Median Absolute Deviation (MAD)54
Skewness5.0066251
Sum22115
Variance1830839.5
MonotonicityDecreasing
2023-12-10T23:03:34.656248image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
373 2
 
6.7%
333 2
 
6.7%
366 1
 
3.3%
270 1
 
3.3%
274 1
 
3.3%
278 1
 
3.3%
290 1
 
3.3%
317 1
 
3.3%
321 1
 
3.3%
327 1
 
3.3%
Other values (18) 18
60.0%
ValueCountFrequency (%)
270 1
3.3%
274 1
3.3%
278 1
3.3%
290 1
3.3%
317 1
3.3%
321 1
3.3%
327 1
3.3%
333 2
6.7%
345 1
3.3%
349 1
3.3%
ValueCountFrequency (%)
7690 1
3.3%
1530 1
3.3%
1437 1
3.3%
1183 1
3.3%
838 1
3.3%
686 1
3.3%
503 1
3.3%
468 1
3.3%
463 1
3.3%
448 1
3.3%

단어중요도
Real number (ℝ)

HIGH CORRELATION 

Distinct26
Distinct (%)86.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.02641
Minimum0.0213
Maximum0.0452
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T23:03:34.822554image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.0213
5-th percentile0.02195
Q10.023825
median0.02505
Q30.02675
95-th percentile0.03469
Maximum0.0452
Range0.0239
Interquartile range (IQR)0.002925

Descriptive statistics

Standard deviation0.0048875881
Coefficient of variation (CV)0.18506581
Kurtosis7.5764826
Mean0.02641
Median Absolute Deviation (MAD)0.00135
Skewness2.515336
Sum0.7923
Variance2.3888517 × 10-5
MonotonicityNot monotonic
2023-12-10T23:03:35.006780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
0.0248 2
 
6.7%
0.0263 2
 
6.7%
0.0253 2
 
6.7%
0.0225 2
 
6.7%
0.0304 1
 
3.3%
0.0239 1
 
3.3%
0.0247 1
 
3.3%
0.0245 1
 
3.3%
0.0213 1
 
3.3%
0.0257 1
 
3.3%
Other values (16) 16
53.3%
ValueCountFrequency (%)
0.0213 1
3.3%
0.0215 1
3.3%
0.0225 2
6.7%
0.0232 1
3.3%
0.0235 1
3.3%
0.0236 1
3.3%
0.0238 1
3.3%
0.0239 1
3.3%
0.0243 1
3.3%
0.0245 1
3.3%
ValueCountFrequency (%)
0.0452 1
3.3%
0.0382 1
3.3%
0.0304 1
3.3%
0.0302 1
3.3%
0.0301 1
3.3%
0.029 1
3.3%
0.0288 1
3.3%
0.0269 1
3.3%
0.0263 2
6.7%
0.0257 1
3.3%

연결정도중심성
Real number (ℝ)

HIGH CORRELATION 

Distinct21
Distinct (%)70.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.078446667
Minimum0.0349
Maximum0.3688
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T23:03:35.204993image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.0349
5-th percentile0.0349
Q10.045875
median0.06375
Q30.07645
95-th percentile0.15432
Maximum0.3688
Range0.3339
Interquartile range (IQR)0.030575

Descriptive statistics

Standard deviation0.063053878
Coefficient of variation (CV)0.80378021
Kurtosis16.00459
Mean0.078446667
Median Absolute Deviation (MAD)0.01315
Skewness3.6849288
Sum2.3534
Variance0.0039757915
MonotonicityNot monotonic
2023-12-10T23:03:35.530772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
0.0611 3
 
10.0%
0.0349 3
 
10.0%
0.0769 2
 
6.7%
0.0437 2
 
6.7%
0.0751 2
 
6.7%
0.0402 2
 
6.7%
0.0664 2
 
6.7%
0.0681 1
 
3.3%
0.0629 1
 
3.3%
0.0576 1
 
3.3%
Other values (11) 11
36.7%
ValueCountFrequency (%)
0.0349 3
10.0%
0.0402 2
6.7%
0.0419 1
 
3.3%
0.0437 2
6.7%
0.0524 1
 
3.3%
0.0559 1
 
3.3%
0.0576 1
 
3.3%
0.0611 3
10.0%
0.0629 1
 
3.3%
0.0646 1
 
3.3%
ValueCountFrequency (%)
0.3688 1
3.3%
0.159 1
3.3%
0.1486 1
3.3%
0.1381 1
3.3%
0.0926 1
3.3%
0.0804 1
3.3%
0.0769 2
6.7%
0.0751 2
6.7%
0.0699 1
3.3%
0.0681 1
3.3%

매개중심성
Real number (ℝ)

HIGH CORRELATION 

Distinct27
Distinct (%)90.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.032993333
Minimum0.0035
Maximum0.4215
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T23:03:35.799018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.0035
5-th percentile0.004595
Q10.010125
median0.0141
Q30.02135
95-th percentile0.06902
Maximum0.4215
Range0.418
Interquartile range (IQR)0.011225

Descriptive statistics

Standard deviation0.075435599
Coefficient of variation (CV)2.2863891
Kurtosis26.519329
Mean0.032993333
Median Absolute Deviation (MAD)0.00565
Skewness5.0350678
Sum0.9898
Variance0.0056905296
MonotonicityNot monotonic
2023-12-10T23:03:35.989554image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
0.0141 3
 
10.0%
0.006 2
 
6.7%
0.4215 1
 
3.3%
0.0118 1
 
3.3%
0.0041 1
 
3.3%
0.0115 1
 
3.3%
0.0102 1
 
3.3%
0.0081 1
 
3.3%
0.0217 1
 
3.3%
0.0161 1
 
3.3%
Other values (17) 17
56.7%
ValueCountFrequency (%)
0.0035 1
3.3%
0.0041 1
3.3%
0.0052 1
3.3%
0.006 2
6.7%
0.0081 1
3.3%
0.0093 1
3.3%
0.0101 1
3.3%
0.0102 1
3.3%
0.0103 1
3.3%
0.0112 1
3.3%
ValueCountFrequency (%)
0.4215 1
3.3%
0.071 1
3.3%
0.0666 1
3.3%
0.0597 1
3.3%
0.0375 1
3.3%
0.0297 1
3.3%
0.0284 1
3.3%
0.0217 1
3.3%
0.0203 1
3.3%
0.0194 1
3.3%

Interactions

2023-12-10T23:03:31.363340image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:03:28.398768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:03:29.140104image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:03:29.956466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:03:30.678835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:03:31.508806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:03:28.532375image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:03:29.294928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:03:30.135630image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:03:30.814217image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:03:31.664347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:03:28.673823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:03:29.472860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:03:30.278803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:03:30.963471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:03:31.795848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:03:28.838954image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:03:29.598359image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:03:30.404795image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:03:31.104644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:03:31.946943image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:03:28.985689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:03:29.793180image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:03:30.541950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:03:31.237962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T23:03:36.134882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
분석인덱스키워드명단어빈도단어중요도연결정도중심성매개중심성
분석인덱스1.0001.0000.5750.0000.5960.590
키워드명1.0001.0001.0001.0001.0001.000
단어빈도0.5751.0001.0000.0001.0001.000
단어중요도0.0001.0000.0001.0000.2650.000
연결정도중심성0.5961.0001.0000.2651.0001.000
매개중심성0.5901.0001.0000.0001.0001.000
2023-12-10T23:03:36.371379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
분석인덱스단어빈도단어중요도연결정도중심성매개중심성
분석인덱스1.000-1.000-0.047-0.639-0.566
단어빈도-1.0001.0000.0510.6390.568
단어중요도-0.0470.0511.000-0.0260.530
연결정도중심성-0.6390.639-0.0261.0000.513
매개중심성-0.5660.5680.5300.5131.000

Missing values

2023-12-10T23:03:32.530035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T23:03:32.731233image/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
012010-01고양76900.03040.36880.4215
122010-01경기15300.02510.1590.071
232010-01경기도14370.02380.14860.0666
342010-01서울11830.02480.13810.0597
452010-01분양8380.03020.05590.0203
562010-01파주6860.02630.08040.0194
672010-01아파트5030.02530.07510.0284
782010-01수도권4680.02250.04190.0093
892010-01수원4630.02250.09260.0141
9102010-01시장4480.02530.06110.0149
분석인덱스수집년월키워드명단어빈도단어중요도연결정도중심성매개중심성
20212010-01김포3450.02560.07690.0101
21222010-01인천3330.02320.06640.0141
22232010-01시민3330.0290.04370.0112
23242010-01문화3270.02690.06110.0161
24252010-01도시3210.02880.05760.0141
25262010-01사업3170.02570.04370.0217
26272010-01용인2900.02130.06290.0081
27282010-01주택2780.02450.04020.0102
28292010-01사랑2740.02630.03490.0115
29302010-01신도시2700.02470.03490.0041