Overview

Dataset statistics

Number of variables4
Number of observations1098
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory35.5 KiB
Average record size in memory33.1 B

Variable types

Categorical2
Numeric1
Text1

Dataset

Description도시재생 사업 지구의 개별 특성 반영을 위해 소지역 단위로 모니터링 주기에 따른 시계열적인 활성화 현황을 파악유동인구, 사업체 수, 카드 매출, 공시지가 집계를 통해 사업 전후의 시계열 분석도시재생 사업 지구의 시계열적 활성화 현황을 파악할 수 있도록 유동인구, 카드 매출, 공시지가 데이터 수집 주기에 맞춰 변화율을 산출
Author국토교통부
URLhttps://www.data.go.kr/data/15123179/fileData.do

Alerts

구분 has constant value ""Constant
변화율 has 46 (4.2%) zerosZeros

Reproduction

Analysis started2023-12-12 01:48:29.595614
Analysis finished2023-12-12 01:48:29.973651
Duration0.38 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

구분
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size8.7 KiB
유동인구 변화율
1098 

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row유동인구 변화율
2nd row유동인구 변화율
3rd row유동인구 변화율
4th row유동인구 변화율
5th row유동인구 변화율

Common Values

ValueCountFrequency (%)
유동인구 변화율 1098
100.0%

Length

2023-12-12T10:48:30.053751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T10:48:30.165726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
유동인구 1098
50.0%
변화율 1098
50.0%

기준년도
Categorical

Distinct3
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size8.7 KiB
2017년
366 
2018년
366 
2016년
366 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2017년
2nd row2018년
3rd row2016년
4th row2017년
5th row2018년

Common Values

ValueCountFrequency (%)
2017년 366
33.3%
2018년 366
33.3%
2016년 366
33.3%

Length

2023-12-12T10:48:30.282915image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T10:48:30.375982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2017년 366
33.3%
2018년 366
33.3%
2016년 366
33.3%

변화율
Real number (ℝ)

ZEROS 

Distinct1027
Distinct (%)93.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean111.84333
Minimum-99.695658
Maximum10281.343
Zeros46
Zeros (%)4.2%
Negative597
Negative (%)54.4%
Memory size9.8 KiB
2023-12-12T10:48:30.496820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-99.695658
5-th percentile-88.830571
Q1-40.600328
median-2.9819887
Q328.740936
95-th percentile495.74423
Maximum10281.343
Range10381.039
Interquartile range (IQR)69.341264

Descriptive statistics

Standard deviation620.70068
Coefficient of variation (CV)5.5497336
Kurtosis102.64507
Mean111.84333
Median Absolute Deviation (MAD)35.828812
Skewness8.8513296
Sum122803.98
Variance385269.34
MonotonicityNot monotonic
2023-12-12T10:48:30.666604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 46
 
4.2%
-0.4578921146074852 2
 
0.2%
-14.15915664318342 2
 
0.2%
-24.15306923615078 2
 
0.2%
26.2982933724218 2
 
0.2%
-24.31836734693879 2
 
0.2%
-24.29578158297978 2
 
0.2%
-0.9028141606166972 2
 
0.2%
16.00880474907713 2
 
0.2%
-44.11702017944929 2
 
0.2%
Other values (1017) 1034
94.2%
ValueCountFrequency (%)
-99.6956584192193 1
0.1%
-99.47412362973968 1
0.1%
-99.259217723948 1
0.1%
-99.20191721380051 1
0.1%
-98.45529780337192 1
0.1%
-98.22913687582222 1
0.1%
-98.15246109439668 1
0.1%
-98.14576572239606 1
0.1%
-98.03664921465968 1
0.1%
-97.84581527780928 1
0.1%
ValueCountFrequency (%)
10281.34328358209 1
0.1%
7177.198525539759 1
0.1%
6117.870868562647 1
0.1%
5283.280809421131 1
0.1%
4505.538334366606 1
0.1%
4298.188248881187 1
0.1%
4212.235403582229 1
0.1%
4006.287683031869 1
0.1%
3260.226364846871 1
0.1%
3213.617508224861 1
0.1%

공간정보
Text

Distinct366
Distinct (%)33.3%
Missing0
Missing (%)0.0%
Memory size8.7 KiB
2023-12-12T10:48:30.936353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length188
Median length187
Mean length186.81421
Min length180

Characters and Unicode

Total characters205122
Distinct characters25
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowMULTIPOLYGON (((127.020298571801 37.2868692443179,127.020298404163 37.2864187589318,127.02086225479 37.2864186332032,127.020862422428 37.2868691604989,127.020298571801 37.2868692443179)))
2nd rowMULTIPOLYGON (((127.020298571801 37.2868692443179,127.020298404163 37.2864187589318,127.02086225479 37.2864186332032,127.020862422428 37.2868691604989,127.020298571801 37.2868692443179)))
3rd rowMULTIPOLYGON (((127.019170870548 37.286869411956,127.01917070291 37.2864189265698,127.019734469717 37.2864188427508,127.019734637355 37.2868693700465,127.019170870548 37.286869411956)))
4th rowMULTIPOLYGON (((127.019170870548 37.286869411956,127.01917070291 37.2864189265698,127.019734469717 37.2864188427508,127.019734637355 37.2868693700465,127.019170870548 37.286869411956)))
5th rowMULTIPOLYGON (((127.019170870548 37.286869411956,127.01917070291 37.2864189265698,127.019734469717 37.2864188427508,127.019734637355 37.2868693700465,127.019170870548 37.286869411956)))
ValueCountFrequency (%)
multipolygon 1098
 
14.3%
127.016349857215 6
 
0.1%
37.28867227551 6
 
0.1%
127.020860913685 6
 
0.1%
127.023117824934 6
 
0.1%
37.2877710951901 6
 
0.1%
127.01466048463 6
 
0.1%
127.018606684645 6
 
0.1%
127.01691471367 6
 
0.1%
37.2855171595167,127.023117489658 3
 
< 0.1%
Other values (2179) 6537
85.1%
2023-12-12T10:48:31.469272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 24345
11.9%
7 23463
11.4%
1 21990
10.7%
8 16374
 
8.0%
3 15834
 
7.7%
0 14877
 
7.3%
6 13158
 
6.4%
9 11469
 
5.6%
4 10992
 
5.4%
. 10980
 
5.4%
Other values (15) 41640
20.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 163398
79.7%
Other Punctuation 15372
 
7.5%
Uppercase Letter 13176
 
6.4%
Space Separator 6588
 
3.2%
Close Punctuation 3294
 
1.6%
Open Punctuation 3294
 
1.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 24345
14.9%
7 23463
14.4%
1 21990
13.5%
8 16374
10.0%
3 15834
9.7%
0 14877
9.1%
6 13158
8.1%
9 11469
7.0%
4 10992
6.7%
5 10896
6.7%
Uppercase Letter
ValueCountFrequency (%)
O 2196
16.7%
L 2196
16.7%
U 1098
8.3%
N 1098
8.3%
G 1098
8.3%
Y 1098
8.3%
P 1098
8.3%
I 1098
8.3%
T 1098
8.3%
M 1098
8.3%
Other Punctuation
ValueCountFrequency (%)
. 10980
71.4%
, 4392
 
28.6%
Space Separator
ValueCountFrequency (%)
6588
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3294
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3294
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 191946
93.6%
Latin 13176
 
6.4%

Most frequent character per script

Common
ValueCountFrequency (%)
2 24345
12.7%
7 23463
12.2%
1 21990
11.5%
8 16374
8.5%
3 15834
8.2%
0 14877
7.8%
6 13158
6.9%
9 11469
6.0%
4 10992
 
5.7%
. 10980
 
5.7%
Other values (5) 28464
14.8%
Latin
ValueCountFrequency (%)
O 2196
16.7%
L 2196
16.7%
U 1098
8.3%
N 1098
8.3%
G 1098
8.3%
Y 1098
8.3%
P 1098
8.3%
I 1098
8.3%
T 1098
8.3%
M 1098
8.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 205122
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 24345
11.9%
7 23463
11.4%
1 21990
10.7%
8 16374
 
8.0%
3 15834
 
7.7%
0 14877
 
7.3%
6 13158
 
6.4%
9 11469
 
5.6%
4 10992
 
5.4%
. 10980
 
5.4%
Other values (15) 41640
20.3%

Interactions

2023-12-12T10:48:29.744455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T10:48:31.590521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기준년도변화율
기준년도1.0000.222
변화율0.2221.000
2023-12-12T10:48:31.701439image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
변화율기준년도
변화율1.0000.143
기준년도0.1431.000

Missing values

2023-12-12T10:48:29.857657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T10:48:29.934780image/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

구분기준년도변화율공간정보
0유동인구 변화율2017년-80.347636MULTIPOLYGON (((127.020298571801 37.2868692443179,127.020298404163 37.2864187589318,127.02086225479 37.2864186332032,127.020862422428 37.2868691604989,127.020298571801 37.2868692443179)))
1유동인구 변화율2018년-0.0MULTIPOLYGON (((127.020298571801 37.2868692443179,127.020298404163 37.2864187589318,127.02086225479 37.2864186332032,127.020862422428 37.2868691604989,127.020298571801 37.2868692443179)))
2유동인구 변화율2016년-38.682094MULTIPOLYGON (((127.019170870548 37.286869411956,127.01917070291 37.2864189265698,127.019734469717 37.2864188427508,127.019734637355 37.2868693700465,127.019170870548 37.286869411956)))
3유동인구 변화율2017년53.085577MULTIPOLYGON (((127.019170870548 37.286869411956,127.01917070291 37.2864189265698,127.019734469717 37.2864188427508,127.019734637355 37.2868693700465,127.019170870548 37.286869411956)))
4유동인구 변화율2018년-32.446646MULTIPOLYGON (((127.019170870548 37.286869411956,127.01917070291 37.2864189265698,127.019734469717 37.2864188427508,127.019734637355 37.2868693700465,127.019170870548 37.286869411956)))
5유동인구 변화율2016년-6.270516MULTIPOLYGON (((127.018043169295 37.2868696634131,127.018042917837 37.2864190942079,127.018606768464 37.2864190522984,127.018606936102 37.2868695795941,127.018043169295 37.2868696634131)))
6유동인구 변화율2017년-99.474124MULTIPOLYGON (((127.018043169295 37.2868696634131,127.018042917837 37.2864190942079,127.018606768464 37.2864190522984,127.018606936102 37.2868695795941,127.018043169295 37.2868696634131)))
7유동인구 변화율2018년0.0MULTIPOLYGON (((127.018043169295 37.2868696634131,127.018042917837 37.2864190942079,127.018606768464 37.2864190522984,127.018606936102 37.2868695795941,127.018043169295 37.2868696634131)))
8유동인구 변화율2016년11.545674MULTIPOLYGON (((127.016915384222 37.2868697891416,127.016915216584 37.2864193037555,127.01747915103 37.2864191780269,127.017479318668 37.2868697053226,127.016915384222 37.2868697891416)))
9유동인구 변화율2017년-94.229524MULTIPOLYGON (((127.016915384222 37.2868697891416,127.016915216584 37.2864193037555,127.01747915103 37.2864191780269,127.017479318668 37.2868697053226,127.016915384222 37.2868697891416)))
구분기준년도변화율공간정보
1088유동인구 변화율2016년3.561233MULTIPOLYGON (((127.019733547708 37.2823641389992,127.01973338007 37.2819136117035,127.020297146877 37.281913569794,127.020297230696 37.2823640970897,127.019733547708 37.2823641389992)))
1089유동인구 변화율2017년8.810026MULTIPOLYGON (((127.019733547708 37.2823641389992,127.01973338007 37.2819136117035,127.020297146877 37.281913569794,127.020297230696 37.2823640970897,127.019733547708 37.2823641389992)))
1090유동인구 변화율2018년-11.257047MULTIPOLYGON (((127.019733547708 37.2823641389992,127.01973338007 37.2819136117035,127.020297146877 37.281913569794,127.020297230696 37.2823640970897,127.019733547708 37.2823641389992)))
1091유동인구 변화율2016년-18.021433MULTIPOLYGON (((127.018605846455 37.2823643485468,127.018605762636 37.2819138212511,127.019169529443 37.2819137374321,127.019169613262 37.2823642228182,127.018605846455 37.2823643485468)))
1092유동인구 변화율2017년-50.113013MULTIPOLYGON (((127.018605846455 37.2823643485468,127.018605762636 37.2819138212511,127.019169529443 37.2819137374321,127.019169613262 37.2823642228182,127.018605846455 37.2823643485468)))
1093유동인구 변화율2018년43.947012MULTIPOLYGON (((127.018605846455 37.2823643485468,127.018605762636 37.2819138212511,127.019169529443 37.2819137374321,127.019169613262 37.2823642228182,127.018605846455 37.2823643485468)))
1094유동인구 변화율2016년-22.916951MULTIPOLYGON (((127.017478145201 37.2823645580944,127.017478061382 37.2819140307987,127.018041912009 37.2819139050701,127.018041995828 37.2823644323658,127.017478145201 37.2823645580944)))
1095유동인구 변화율2017년-32.003005MULTIPOLYGON (((127.017478145201 37.2823645580944,127.017478061382 37.2819140307987,127.018041912009 37.2819139050701,127.018041995828 37.2823644323658,127.017478145201 37.2823645580944)))
1096유동인구 변화율2018년90.78815MULTIPOLYGON (((127.017478145201 37.2823645580944,127.017478061382 37.2819140307987,127.018041912009 37.2819139050701,127.018041995828 37.2823644323658,127.017478145201 37.2823645580944)))
1097유동인구 변화율2016년-33.109531MULTIPOLYGON (((127.016350527767 37.2823646838229,127.016350443948 37.2819141565272,127.016914294575 37.2819141146177,127.016914462213 37.2823646419134,127.016350527767 37.2823646838229)))