Overview

Dataset statistics

Number of variables9
Number of observations10000
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory800.8 KiB
Average record size in memory82.0 B

Variable types

Categorical6
Text1
Numeric2

Dataset

Description경기도 수원시 지역화폐 결제 정보로 지역별(시군구, 읍면동), 업종별, 성별, 연령대별 지역화폐 결제 정보(건수, 금액)를 포함합니다.
Author경기도 수원시
URLhttps://www.data.go.kr/data/15075618/fileData.do

Alerts

데이터기준일자 has constant value ""Constant
결제건수 is highly overall correlated with 결제금액High correlation
결제금액 is highly overall correlated with 결제건수High correlation

Reproduction

Analysis started2023-12-11 23:25:54.648078
Analysis finished2023-12-11 23:25:56.014752
Duration1.37 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

기준년월
Categorical

Distinct13
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2020-06
1061 
2020-05
1052 
2020-10
986 
2020-09
950 
2020-07
939 
Other values (8)
5012 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2020-04
2nd row2019-12
3rd row2020-04
4th row2020-01
5th row2020-02

Common Values

ValueCountFrequency (%)
2020-06 1061
10.6%
2020-05 1052
10.5%
2020-10 986
9.9%
2020-09 950
9.5%
2020-07 939
9.4%
2020-11 932
9.3%
2020-04 912
9.1%
2020-08 829
8.3%
2020-03 595
5.9%
2020-01 485
 
4.9%
Other values (3) 1259
12.6%

Length

2023-12-12T08:25:56.070879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2020-06 1061
10.6%
2020-05 1052
10.5%
2020-10 986
9.9%
2020-09 950
9.5%
2020-07 939
9.4%
2020-11 932
9.3%
2020-04 912
9.1%
2020-08 829
8.3%
2020-03 595
5.9%
2020-01 485
 
4.9%
Other values (3) 1259
12.6%

시군구명
Categorical

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
팔달구
3194 
권선구
2806 
장안구
2243 
영통구
1757 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row권선구
2nd row팔달구
3rd row팔달구
4th row팔달구
5th row장안구

Common Values

ValueCountFrequency (%)
팔달구 3194
31.9%
권선구 2806
28.1%
장안구 2243
22.4%
영통구 1757
17.6%

Length

2023-12-12T08:25:56.169298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T08:25:56.258308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
팔달구 3194
31.9%
권선구 2806
28.1%
장안구 2243
22.4%
영통구 1757
17.6%

읍면동명
Text

Distinct56
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-12T08:25:56.461230image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
Mean length3.1409
Min length2

Characters and Unicode

Total characters31409
Distinct characters74
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
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 row호매실동
2nd row남창동
3rd row남창동
4th row신풍동
5th row송죽동
ValueCountFrequency (%)
권선동 346
 
3.5%
영통동 326
 
3.3%
정자동 325
 
3.2%
매탄동 316
 
3.2%
인계동 312
 
3.1%
조원동 286
 
2.9%
화서동 278
 
2.8%
망포동 274
 
2.7%
우만동 273
 
2.7%
금곡동 271
 
2.7%
Other values (46) 6993
69.9%
2023-12-12T08:25:56.806437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 9062
28.9%
매 1322
 
4.2%
천 985
 
3.1%
로 938
 
3.0%
가 938
 
3.0%
영 772
 
2.5%
산 566
 
1.8%
원 529
 
1.7%
화 529
 
1.7%
정 523
 
1.7%
Other values (64) 15245
48.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 30471
97.0%
Decimal Number 938
 
3.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 9062
29.7%
매 1322
 
4.3%
천 985
 
3.2%
로 938
 
3.1%
가 938
 
3.1%
영 772
 
2.5%
산 566
 
1.9%
원 529
 
1.7%
화 529
 
1.7%
정 523
 
1.7%
Other values (61) 14307
47.0%
Decimal Number
ValueCountFrequency (%)
1 331
35.3%
2 321
34.2%
3 286
30.5%

Most occurring scripts

ValueCountFrequency (%)
Hangul 30471
97.0%
Common 938
 
3.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 9062
29.7%
매 1322
 
4.3%
천 985
 
3.2%
로 938
 
3.1%
가 938
 
3.1%
영 772
 
2.5%
산 566
 
1.9%
원 529
 
1.7%
화 529
 
1.7%
정 523
 
1.7%
Other values (61) 14307
47.0%
Common
ValueCountFrequency (%)
1 331
35.3%
2 321
34.2%
3 286
30.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 30471
97.0%
ASCII 938
 
3.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 9062
29.7%
매 1322
 
4.3%
천 985
 
3.2%
로 938
 
3.1%
가 938
 
3.1%
영 772
 
2.5%
산 566
 
1.9%
원 529
 
1.7%
화 529
 
1.7%
정 523
 
1.7%
Other values (61) 14307
47.0%
ASCII
ValueCountFrequency (%)
1 331
35.3%
2 321
34.2%
3 286
30.5%

성별
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
여
5019 
남
4981 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row여
2nd row남
3rd row여
4th row여
5th row남

Common Values

ValueCountFrequency (%)
여 5019
50.2%
남 4981
49.8%

Length

2023-12-12T08:25:56.925186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T08:25:57.009776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
여 5019
50.2%
남 4981
49.8%

연령대
Categorical

Distinct7
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
20대
1994 
40대
1967 
30대
1889 
50대
1869 
60대이상
1461 
Other values (2)
820 

Length

Max length5
Median length3
Mean length3.2924
Min length3

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row60대이상
2nd row40대
3rd row40대
4th row40대
5th row40대

Common Values

ValueCountFrequency (%)
20대 1994
19.9%
40대 1967
19.7%
30대 1889
18.9%
50대 1869
18.7%
60대이상 1461
14.6%
10대 819
8.2%
10세미만 1
 
< 0.1%

Length

2023-12-12T08:25:57.117598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T08:25:57.229479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
20대 1994
19.9%
40대 1967
19.7%
30대 1889
18.9%
50대 1869
18.7%
60대이상 1461
14.6%
10대 819
8.2%
10세미만 1
 
< 0.1%

업종명
Categorical

Distinct34
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
일반·휴게음식
776 
유통업영리
751 
음료식품
 
646
보건위생
 
589
약국
 
571
Other values (29)
6667 

Length

Max length8
Median length7
Mean length4.2049
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row일반·휴게음식
2nd row유통업영리
3rd row의류
4th row일반·휴게음식
5th row일반·휴게음식

Common Values

ValueCountFrequency (%)
일반·휴게음식 776
 
7.8%
유통업영리 751
 
7.5%
음료식품 646
 
6.5%
보건위생 589
 
5.9%
약국 571
 
5.7%
의원 537
 
5.4%
레져업소 496
 
5.0%
문화·취미 419
 
4.2%
신변잡화 414
 
4.1%
수리서비스 405
 
4.0%
Other values (24) 4396
44.0%

Length

2023-12-12T08:25:57.362672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
일반·휴게음식 776
 
7.8%
유통업영리 751
 
7.5%
음료식품 646
 
6.5%
보건위생 589
 
5.9%
약국 571
 
5.7%
의원 537
 
5.4%
레져업소 496
 
5.0%
문화·취미 419
 
4.2%
신변잡화 414
 
4.1%
수리서비스 405
 
4.0%
Other values (24) 4396
44.0%

결제건수
Real number (ℝ)

HIGH CORRELATION 

Distinct827
Distinct (%)8.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean104.7539
Minimum1
Maximum9170
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T08:25:57.486286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median8
Q338
95-th percentile463.1
Maximum9170
Range9169
Interquartile range (IQR)36

Descriptive statistics

Standard deviation411.76671
Coefficient of variation (CV)3.9308008
Kurtosis114.40729
Mean104.7539
Median Absolute Deviation (MAD)7
Skewness9.0510368
Sum1047539
Variance169551.83
MonotonicityNot monotonic
2023-12-12T08:25:57.648038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1668
 
16.7%
2 1053
 
10.5%
3 689
 
6.9%
4 540
 
5.4%
5 410
 
4.1%
6 310
 
3.1%
7 248
 
2.5%
8 246
 
2.5%
10 203
 
2.0%
9 167
 
1.7%
Other values (817) 4466
44.7%
ValueCountFrequency (%)
1 1668
16.7%
2 1053
10.5%
3 689
6.9%
4 540
 
5.4%
5 410
 
4.1%
6 310
 
3.1%
7 248
 
2.5%
8 246
 
2.5%
9 167
 
1.7%
10 203
 
2.0%
ValueCountFrequency (%)
9170 1
< 0.1%
7836 1
< 0.1%
7781 1
< 0.1%
7463 1
< 0.1%
6335 1
< 0.1%
6042 1
< 0.1%
6011 1
< 0.1%
5712 1
< 0.1%
5274 1
< 0.1%
5225 1
< 0.1%

결제금액
Real number (ℝ)

HIGH CORRELATION 

Distinct6303
Distinct (%)63.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2131356.5
Minimum10
Maximum2.167032 × 108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T08:25:57.802758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10
5-th percentile8000
Q155000
median261700
Q31132735.5
95-th percentile9218130
Maximum2.167032 × 108
Range2.1670319 × 108
Interquartile range (IQR)1077735.5

Descriptive statistics

Standard deviation8157715.3
Coefficient of variation (CV)3.8274757
Kurtosis186.62808
Mean2131356.5
Median Absolute Deviation (MAD)242300
Skewness11.320229
Sum2.1313565 × 1010
Variance6.6548319 × 1013
MonotonicityNot monotonic
2023-12-12T08:25:57.953470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20000 94
 
0.9%
10000 75
 
0.8%
15000 69
 
0.7%
40000 62
 
0.6%
5000 60
 
0.6%
30000 59
 
0.6%
50000 54
 
0.5%
6000 54
 
0.5%
12000 46
 
0.5%
100000 46
 
0.5%
Other values (6293) 9381
93.8%
ValueCountFrequency (%)
10 2
 
< 0.1%
100 2
 
< 0.1%
120 1
 
< 0.1%
220 1
 
< 0.1%
500 1
 
< 0.1%
600 1
 
< 0.1%
700 1
 
< 0.1%
800 1
 
< 0.1%
1000 20
0.2%
1100 1
 
< 0.1%
ValueCountFrequency (%)
216703200 1
< 0.1%
206980345 1
< 0.1%
151700738 1
< 0.1%
150975010 1
< 0.1%
149331170 1
< 0.1%
148767881 1
< 0.1%
147837290 1
< 0.1%
122006680 1
< 0.1%
109950860 1
< 0.1%
106060936 1
< 0.1%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2020-12-11
10000 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2020-12-11
2nd row2020-12-11
3rd row2020-12-11
4th row2020-12-11
5th row2020-12-11

Common Values

ValueCountFrequency (%)
2020-12-11 10000
100.0%

Length

2023-12-12T08:25:58.104153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T08:25:58.277966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2020-12-11 10000
100.0%

Interactions

2023-12-12T08:25:55.563802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:25:55.385389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:25:55.644007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:25:55.479136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T08:25:58.355661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기준년월시군구명읍면동명성별연령대업종명결제건수결제금액
기준년월1.0000.0850.0910.0190.1140.1630.0570.048
시군구명0.0851.0001.0000.0000.0410.2450.0720.083
읍면동명0.0911.0001.0000.0210.0870.4900.1250.110
성별0.0190.0000.0211.0000.0260.0790.0110.000
연령대0.1140.0410.0870.0261.0000.1900.0580.063
업종명0.1630.2450.4900.0790.1901.0000.2670.218
결제건수0.0570.0720.1250.0110.0580.2671.0000.889
결제금액0.0480.0830.1100.0000.0630.2180.8891.000
2023-12-12T08:25:58.515395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군구명업종명기준년월성별연령대
시군구명1.0000.1270.0500.0000.028
업종명0.1271.0000.0510.0630.079
기준년월0.0500.0511.0000.0180.053
성별0.0000.0630.0181.0000.027
연령대0.0280.0790.0530.0271.000
2023-12-12T08:25:58.647207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
결제건수결제금액기준년월시군구명성별연령대업종명
결제건수1.0000.8370.0240.0460.0110.0300.102
결제금액0.8371.0000.0200.0530.0000.0330.082
기준년월0.0240.0201.0000.0500.0180.0530.051
시군구명0.0460.0530.0501.0000.0000.0280.127
성별0.0110.0000.0180.0001.0000.0270.063
연령대0.0300.0330.0530.0280.0271.0000.079
업종명0.1020.0820.0510.1270.0630.0791.000

Missing values

2023-12-12T08:25:55.769513image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T08:25:55.959627image/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

기준년월시군구명읍면동명성별연령대업종명결제건수결제금액데이터기준일자
698862020-04권선구호매실동여60대이상일반·휴게음식8225391002020-12-11
950202019-12팔달구남창동남40대유통업영리5650702020-12-11
736842020-04팔달구남창동여40대의류124760002020-12-11
905192020-01팔달구신풍동여40대일반·휴게음식286299002020-12-11
840312020-02장안구송죽동남40대일반·휴게음식12632469702020-12-11
784852020-03영통구이의동남60대이상문화·취미41200002020-12-11
975552019-11권선구호매실동남40대자동차정비·유지2750002020-12-11
358112020-08팔달구인계동남20대기타84130002020-12-11
265202020-09팔달구영동남30대광학제품2600002020-12-11
801292020-03팔달구남창동남40대신변잡화6310002020-12-11
기준년월시군구명읍면동명성별연령대업종명결제건수결제금액데이터기준일자
597432020-05권선구호매실동여50대용역서비스41770002020-12-11
47762020-11장안구영화동남50대유통업영리90085780402020-12-11
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