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/ebd237d7-a8ef-476e-bcc4-6dba6cabeb7d

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

Reproduction

Analysis started2023-12-10 13:58:52.905258
Analysis finished2023-12-10 13:58:58.177552
Duration5.27 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
2023-12-10T22:58:58.321445image/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
2023-12-10T22:58:58.541435image/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
2023-12-10T22:58:58.784499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:58:58.949519image/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
2023-12-10T22:58:59.286352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length2
Mean length2.2
Min length1

Characters and Unicode

Total characters66
Distinct characters47
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 row맛집
2nd row경기도
3rd row음식점
4th row음식
5th row수원
ValueCountFrequency (%)
맛집 1
 
3.3%
경기도 1
 
3.3%
화성 1
 
3.3%
파주 1
 
3.3%
배달 1
 
3.3%
양평 1
 
3.3%
전문점 1
 
3.3%
가평 1
 
3.3%
부천 1
 
3.3%
안산 1
 
3.3%
Other values (20) 20
66.7%
2023-12-10T22:58:59.854111image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
양 4
 
6.1%
주 3
 
4.5%
음 3
 
4.5%
식 3
 
4.5%
점 3
 
4.5%
맛 2
 
3.0%
안 2
 
3.0%
남 2
 
3.0%
성 2
 
3.0%
평 2
 
3.0%
Other values (37) 40
60.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 66
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
양 4
 
6.1%
주 3
 
4.5%
음 3
 
4.5%
식 3
 
4.5%
점 3
 
4.5%
맛 2
 
3.0%
안 2
 
3.0%
남 2
 
3.0%
성 2
 
3.0%
평 2
 
3.0%
Other values (37) 40
60.6%

Most occurring scripts

ValueCountFrequency (%)
Hangul 66
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
양 4
 
6.1%
주 3
 
4.5%
음 3
 
4.5%
식 3
 
4.5%
점 3
 
4.5%
맛 2
 
3.0%
안 2
 
3.0%
남 2
 
3.0%
성 2
 
3.0%
평 2
 
3.0%
Other values (37) 40
60.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 66
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
양 4
 
6.1%
주 3
 
4.5%
음 3
 
4.5%
식 3
 
4.5%
점 3
 
4.5%
맛 2
 
3.0%
안 2
 
3.0%
남 2
 
3.0%
성 2
 
3.0%
평 2
 
3.0%
Other values (37) 40
60.6%

단어빈도
Real number (ℝ)

HIGH CORRELATION 

Distinct27
Distinct (%)90.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean252.86667
Minimum74
Maximum1728
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T22:59:00.140712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum74
5-th percentile78
Q187.25
median110.5
Q3162.25
95-th percentile1335.2
Maximum1728
Range1654
Interquartile range (IQR)75

Descriptive statistics

Standard deviation424.64222
Coefficient of variation (CV)1.6793128
Kurtosis9.1440692
Mean252.86667
Median Absolute Deviation (MAD)27.5
Skewness3.1545059
Sum7586
Variance180321.02
MonotonicityDecreasing
2023-12-10T22:59:00.480599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
78 2
 
6.7%
84 2
 
6.7%
110 2
 
6.7%
1728 1
 
3.3%
1724 1
 
3.3%
74 1
 
3.3%
79 1
 
3.3%
82 1
 
3.3%
87 1
 
3.3%
88 1
 
3.3%
Other values (17) 17
56.7%
ValueCountFrequency (%)
74 1
3.3%
78 2
6.7%
79 1
3.3%
82 1
3.3%
84 2
6.7%
87 1
3.3%
88 1
3.3%
96 1
3.3%
105 1
3.3%
107 1
3.3%
ValueCountFrequency (%)
1728 1
3.3%
1724 1
3.3%
860 1
3.3%
231 1
3.3%
214 1
3.3%
209 1
3.3%
192 1
3.3%
165 1
3.3%
154 1
3.3%
141 1
3.3%

단어중요도
Real number (ℝ)

Distinct28
Distinct (%)93.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.03024
Minimum0.0227
Maximum0.0419
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T22:59:00.794264image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.0227
5-th percentile0.02369
Q10.0255
median0.0307
Q30.03385
95-th percentile0.04062
Maximum0.0419
Range0.0192
Interquartile range (IQR)0.00835

Descriptive statistics

Standard deviation0.005469199
Coefficient of variation (CV)0.18085976
Kurtosis-0.5623063
Mean0.03024
Median Absolute Deviation (MAD)0.00455
Skewness0.53047443
Sum0.9072
Variance2.9912138 × 10-5
MonotonicityNot monotonic
2023-12-10T22:59:01.014633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
0.032 2
 
6.7%
0.0261 2
 
6.7%
0.0417 1
 
3.3%
0.0393 1
 
3.3%
0.0348 1
 
3.3%
0.0343 1
 
3.3%
0.0227 1
 
3.3%
0.0286 1
 
3.3%
0.034 1
 
3.3%
0.0329 1
 
3.3%
Other values (18) 18
60.0%
ValueCountFrequency (%)
0.0227 1
3.3%
0.0236 1
3.3%
0.0238 1
3.3%
0.0241 1
3.3%
0.0244 1
3.3%
0.0247 1
3.3%
0.0252 1
3.3%
0.0253 1
3.3%
0.0261 2
6.7%
0.0262 1
3.3%
ValueCountFrequency (%)
0.0419 1
3.3%
0.0417 1
3.3%
0.0393 1
3.3%
0.036 1
3.3%
0.0359 1
3.3%
0.0348 1
3.3%
0.0343 1
3.3%
0.034 1
3.3%
0.0334 1
3.3%
0.0329 1
3.3%

연결정도중심성
Real number (ℝ)

HIGH CORRELATION 

Distinct23
Distinct (%)76.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.04471
Minimum0.0084
Maximum0.2661
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T22:59:01.335315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.0084
5-th percentile0.0112
Q10.0182
median0.0266
Q30.04025
95-th percentile0.1764
Maximum0.2661
Range0.2577
Interquartile range (IQR)0.02205

Descriptive statistics

Standard deviation0.057816167
Coefficient of variation (CV)1.2931373
Kurtosis8.5146653
Mean0.04471
Median Absolute Deviation (MAD)0.0084
Skewness2.9426553
Sum1.3413
Variance0.0033427092
MonotonicityNot monotonic
2023-12-10T22:59:01.606153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
0.0294 3
 
10.0%
0.0182 3
 
10.0%
0.0112 2
 
6.7%
0.0196 2
 
6.7%
0.0266 2
 
6.7%
0.2661 1
 
3.3%
0.0224 1
 
3.3%
0.0154 1
 
3.3%
0.0546 1
 
3.3%
0.021 1
 
3.3%
Other values (13) 13
43.3%
ValueCountFrequency (%)
0.0084 1
 
3.3%
0.0112 2
6.7%
0.0126 1
 
3.3%
0.0154 1
 
3.3%
0.0168 1
 
3.3%
0.0182 3
10.0%
0.0196 2
6.7%
0.021 1
 
3.3%
0.0224 1
 
3.3%
0.0252 1
 
3.3%
ValueCountFrequency (%)
0.2661 1
3.3%
0.2016 1
3.3%
0.1456 1
3.3%
0.0574 1
3.3%
0.0546 1
3.3%
0.0518 1
3.3%
0.0434 1
3.3%
0.042 1
3.3%
0.035 1
3.3%
0.0336 1
3.3%

매개중심성
Real number (ℝ)

HIGH CORRELATION 

Distinct29
Distinct (%)96.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.040926667
Minimum0.0002
Maximum0.3772
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T22:59:01.823990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.0002
5-th percentile0.00058
Q10.003075
median0.01125
Q30.031325
95-th percentile0.226185
Maximum0.3772
Range0.377
Interquartile range (IQR)0.02825

Descriptive statistics

Standard deviation0.084462822
Coefficient of variation (CV)2.0637601
Kurtosis9.8558337
Mean0.040926667
Median Absolute Deviation (MAD)0.01005
Skewness3.1500579
Sum1.2278
Variance0.0071339682
MonotonicityNot monotonic
2023-12-10T22:59:02.443055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
0.0014 2
 
6.7%
0.2688 1
 
3.3%
0.0002 1
 
3.3%
0.0077 1
 
3.3%
0.0122 1
 
3.3%
0.0222 1
 
3.3%
0.0532 1
 
3.3%
0.0008 1
 
3.3%
0.0082 1
 
3.3%
0.0067 1
 
3.3%
Other values (19) 19
63.3%
ValueCountFrequency (%)
0.0002 1
3.3%
0.0004 1
3.3%
0.0008 1
3.3%
0.001 1
3.3%
0.0014 2
6.7%
0.0029 1
3.3%
0.003 1
3.3%
0.0033 1
3.3%
0.0057 1
3.3%
0.0067 1
3.3%
ValueCountFrequency (%)
0.3772 1
3.3%
0.2688 1
3.3%
0.1741 1
3.3%
0.0532 1
3.3%
0.0464 1
3.3%
0.0399 1
3.3%
0.0367 1
3.3%
0.0327 1
3.3%
0.0272 1
3.3%
0.0254 1
3.3%

Interactions

2023-12-10T22:58:56.839496image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:58:53.292834image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:58:54.084054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:58:54.928875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:58:55.968724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:58:57.138905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:58:53.440858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:58:54.277771image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:58:55.106203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:58:56.182792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:58:57.298136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:58:53.604279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:58:54.439228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:58:55.307208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:58:56.318819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:58:57.492703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:58:53.772611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:58:54.606884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:58:55.540920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:58:56.480488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:58:57.631536image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:58:53.922375image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:58:54.768363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:58:55.734309image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:58:56.649719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T22:59:02.615975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
분석인덱스키워드명단어빈도단어중요도연결정도중심성매개중심성
분석인덱스1.0001.0000.6810.5310.3960.310
키워드명1.0001.0001.0001.0001.0001.000
단어빈도0.6811.0001.0000.0001.0001.000
단어중요도0.5311.0000.0001.0000.0000.243
연결정도중심성0.3961.0001.0000.0001.0000.992
매개중심성0.3101.0001.0000.2430.9921.000
2023-12-10T22:59:02.805977image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
분석인덱스단어빈도단어중요도연결정도중심성매개중심성
분석인덱스1.000-1.0000.301-0.587-0.554
단어빈도-1.0001.000-0.3040.5910.560
단어중요도0.301-0.3041.000-0.269-0.362
연결정도중심성-0.5870.591-0.2691.0000.899
매개중심성-0.5540.560-0.3620.8991.000

Missing values

2023-12-10T22:58:57.852717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T22:58:58.101259image/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
012010-01맛집17280.04170.26610.3772
122010-01경기도17240.02520.20160.2688
232010-01음식점8600.02530.14560.1741
342010-01음식2310.02470.04340.0327
452010-01수원2140.03190.02940.0254
562010-01게2090.02380.02940.0272
672010-01서울1920.02610.0350.0203
782010-01요리1650.03590.05740.0464
892010-01성남1540.0270.01820.003
9102010-01카페1410.02620.03360.0399
분석인덱스수집년월키워드명단어빈도단어중요도연결정도중심성매개중심성
20212010-01여행960.02610.03080.0162
21222010-01안산880.03040.0210.0067
22232010-01부천870.03290.01960.0082
23242010-01가평840.0340.01120.0008
24252010-01전문점840.02860.05460.0532
25262010-01양평820.0320.01960.0014
26272010-01배달790.02270.02940.0222
27282010-01파주780.03430.02660.0122
28292010-01화성780.03480.01540.0077
29302010-01의왕740.03930.01120.0002