Overview

Dataset statistics

Number of variables6
Number of observations151
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory7.8 KiB
Average record size in memory52.9 B

Variable types

Numeric4
Categorical1
Text1

Dataset

Description경기도 이천시 관내 지역화폐 발행 및 이용 현황으로 사용순위, 업종, 코드, 세부업종, 총사용금액, 사용비율에 대한 정보를 제공하고 있습니다.
Author경기도 이천시
URLhttps://www.data.go.kr/data/15038114/fileData.do

Alerts

순번 is highly overall correlated with 총 사용금액 and 1 other fieldsHigh correlation
코드 is highly overall correlated with 업종High correlation
총 사용금액 is highly overall correlated with 순번 and 1 other fieldsHigh correlation
사용비율 is highly overall correlated with 순번 and 1 other fieldsHigh correlation
업종 is highly overall correlated with 코드High correlation
순번 has unique valuesUnique
코드 has unique valuesUnique
총 사용금액 has unique valuesUnique
사용비율 has 18 (11.9%) zerosZeros

Reproduction

Analysis started2023-12-12 03:20:42.108702
Analysis finished2023-12-12 03:20:44.025628
Duration1.92 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct151
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean76
Minimum1
Maximum151
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2023-12-12T12:20:44.096723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile8.5
Q138.5
median76
Q3113.5
95-th percentile143.5
Maximum151
Range150
Interquartile range (IQR)75

Descriptive statistics

Standard deviation43.734045
Coefficient of variation (CV)0.57544796
Kurtosis-1.2
Mean76
Median Absolute Deviation (MAD)38
Skewness0
Sum11476
Variance1912.6667
MonotonicityStrictly increasing
2023-12-12T12:20:44.217839image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.7%
105 1
 
0.7%
98 1
 
0.7%
99 1
 
0.7%
100 1
 
0.7%
101 1
 
0.7%
102 1
 
0.7%
103 1
 
0.7%
104 1
 
0.7%
106 1
 
0.7%
Other values (141) 141
93.4%
ValueCountFrequency (%)
1 1
0.7%
2 1
0.7%
3 1
0.7%
4 1
0.7%
5 1
0.7%
6 1
0.7%
7 1
0.7%
8 1
0.7%
9 1
0.7%
10 1
0.7%
ValueCountFrequency (%)
151 1
0.7%
150 1
0.7%
149 1
0.7%
148 1
0.7%
147 1
0.7%
146 1
0.7%
145 1
0.7%
144 1
0.7%
143 1
0.7%
142 1
0.7%

업종
Categorical

HIGH CORRELATION 

Distinct37
Distinct (%)24.5%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
용역서비스
12 
의원
11 
일반/휴게 음식
10 
문화/취미
10 
미용/위생
 
9
Other values (32)
99 

Length

Max length10
Median length9
Mean length4.8874172
Min length2

Unique

Unique7 ?
Unique (%)4.6%

Sample

1st row일반/휴게 음식
2nd row학원
3rd row일반유통
4th row학원
5th row의원

Common Values

ValueCountFrequency (%)
용역서비스 12
 
7.9%
의원 11
 
7.3%
일반/휴게 음식 10
 
6.6%
문화/취미 10
 
6.6%
미용/위생 9
 
6.0%
레저/스포츠 서비스 9
 
6.0%
신변잡화 8
 
5.3%
의류 7
 
4.6%
학원 7
 
4.6%
음료/식품 6
 
4.0%
Other values (27) 62
41.1%

Length

2023-12-12T12:20:44.344130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
용역서비스 12
 
6.7%
의원 11
 
6.2%
일반/휴게 10
 
5.6%
음식 10
 
5.6%
문화/취미 10
 
5.6%
미용/위생 9
 
5.1%
레저/스포츠 9
 
5.1%
서비스 9
 
5.1%
신변잡화 8
 
4.5%
학원 7
 
3.9%
Other values (32) 83
46.6%

코드
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct151
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5446.9404
Minimum5
Maximum9401
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2023-12-12T12:20:44.473715image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5
5-th percentile1405
Q13102.5
median5205
Q38103.5
95-th percentile9009.5
Maximum9401
Range9396
Interquartile range (IQR)5001

Descriptive statistics

Standard deviation2537.1202
Coefficient of variation (CV)0.46578813
Kurtosis-1.2136171
Mean5446.9404
Median Absolute Deviation (MAD)2197
Skewness-0.13754867
Sum822488
Variance6436978.9
MonotonicityNot monotonic
2023-12-12T12:20:44.606299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3001 1
 
0.7%
2101 1
 
0.7%
7203 1
 
0.7%
8106 1
 
0.7%
6303 1
 
0.7%
9013 1
 
0.7%
7002 1
 
0.7%
4003 1
 
0.7%
9005 1
 
0.7%
7105 1
 
0.7%
Other values (141) 141
93.4%
ValueCountFrequency (%)
5 1
0.7%
1002 1
0.7%
1004 1
0.7%
1201 1
0.7%
1301 1
0.7%
1302 1
0.7%
1303 1
0.7%
1404 1
0.7%
1406 1
0.7%
1501 1
0.7%
ValueCountFrequency (%)
9401 1
0.7%
9301 1
0.7%
9106 1
0.7%
9105 1
0.7%
9013 1
0.7%
9012 1
0.7%
9011 1
0.7%
9010 1
0.7%
9009 1
0.7%
9008 1
0.7%

세부업종
Text

Distinct150
Distinct (%)99.3%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2023-12-12T12:20:44.882311image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length12
Mean length5.384106
Min length2

Characters and Unicode

Total characters813
Distinct characters217
Distinct categories4 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique149 ?
Unique (%)98.7%

Sample

1st row일반한식
2nd row보습/문리계학원
3rd row편의점
4th row예.체능계학원
5th row의원
ValueCountFrequency (%)
기타 7
 
3.8%
판매 7
 
3.8%
전기/전자제품 2
 
1.1%
용품 2
 
1.1%
서비스 2
 
1.1%
학습지 1
 
0.5%
유치원/어린이집/놀이방/놀이시설 1
 
0.5%
안과 1
 
0.5%
통신기기 1
 
0.5%
출판/인쇄/광고 1
 
0.5%
Other values (158) 158
86.3%
2023-12-12T12:20:45.398927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
/ 46
 
5.7%
기 39
 
4.8%
32
 
3.9%
점 22
 
2.7%
타 19
 
2.3%
원 18
 
2.2%
품 18
 
2.2%
판 16
 
2.0%
매 14
 
1.7%
장 13
 
1.6%
Other values (207) 576
70.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 729
89.7%
Other Punctuation 50
 
6.2%
Space Separator 32
 
3.9%
Uppercase Letter 2
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
기 39
 
5.3%
점 22
 
3.0%
타 19
 
2.6%
원 18
 
2.5%
품 18
 
2.5%
판 16
 
2.2%
매 14
 
1.9%
장 13
 
1.8%
스 13
 
1.8%
용 13
 
1.8%
Other values (201) 544
74.6%
Other Punctuation
ValueCountFrequency (%)
/ 46
92.0%
, 3
 
6.0%
. 1
 
2.0%
Uppercase Letter
ValueCountFrequency (%)
G 1
50.0%
P 1
50.0%
Space Separator
ValueCountFrequency (%)
32
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 729
89.7%
Common 82
 
10.1%
Latin 2
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
기 39
 
5.3%
점 22
 
3.0%
타 19
 
2.6%
원 18
 
2.5%
품 18
 
2.5%
판 16
 
2.2%
매 14
 
1.9%
장 13
 
1.8%
스 13
 
1.8%
용 13
 
1.8%
Other values (201) 544
74.6%
Common
ValueCountFrequency (%)
/ 46
56.1%
32
39.0%
, 3
 
3.7%
. 1
 
1.2%
Latin
ValueCountFrequency (%)
G 1
50.0%
P 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 729
89.7%
ASCII 84
 
10.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/ 46
54.8%
32
38.1%
, 3
 
3.6%
. 1
 
1.2%
G 1
 
1.2%
P 1
 
1.2%
Hangul
ValueCountFrequency (%)
기 39
 
5.3%
점 22
 
3.0%
타 19
 
2.6%
원 18
 
2.5%
품 18
 
2.5%
판 16
 
2.2%
매 14
 
1.9%
장 13
 
1.8%
스 13
 
1.8%
용 13
 
1.8%
Other values (201) 544
74.6%

총 사용금액
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct151
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.85518 × 108
Minimum27000
Maximum1.8217374 × 1010
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2023-12-12T12:20:45.584967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum27000
5-th percentile1962250
Q113878235
median67123206
Q34.3768212 × 108
95-th percentile3.0852769 × 109
Maximum1.8217374 × 1010
Range1.8217347 × 1010
Interquartile range (IQR)4.2380389 × 108

Descriptive statistics

Standard deviation1.9267539 × 109
Coefficient of variation (CV)2.8106541
Kurtosis48.752587
Mean6.85518 × 108
Median Absolute Deviation (MAD)62370406
Skewness6.1995737
Sum1.0351322 × 1011
Variance3.7123808 × 1018
MonotonicityStrictly decreasing
2023-12-12T12:20:45.820352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
18217374079 1
 
0.7%
23195800 1
 
0.7%
30555500 1
 
0.7%
30363440 1
 
0.7%
27466000 1
 
0.7%
27319400 1
 
0.7%
27054460 1
 
0.7%
24287260 1
 
0.7%
23296200 1
 
0.7%
22562000 1
 
0.7%
Other values (141) 141
93.4%
ValueCountFrequency (%)
27000 1
0.7%
188000 1
0.7%
401500 1
0.7%
849500 1
0.7%
1361200 1
0.7%
1629700 1
0.7%
1780000 1
0.7%
1829000 1
0.7%
2095500 1
0.7%
2451290 1
0.7%
ValueCountFrequency (%)
18217374079 1
0.7%
9339336325 1
0.7%
6991392136 1
0.7%
6097484981 1
0.7%
4124624481 1
0.7%
3340621152 1
0.7%
3203661407 1
0.7%
3137415362 1
0.7%
3033138364 1
0.7%
3027356101 1
0.7%

사용비율
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct62
Distinct (%)41.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.66178808
Minimum0
Maximum17.6
Zeros18
Zeros (%)11.9%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2023-12-12T12:20:46.048764image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.01
median0.06
Q30.425
95-th percentile2.98
Maximum17.6
Range17.6
Interquartile range (IQR)0.415

Descriptive statistics

Standard deviation1.8612054
Coefficient of variation (CV)2.8123888
Kurtosis48.780456
Mean0.66178808
Median Absolute Deviation (MAD)0.06
Skewness6.2013417
Sum99.93
Variance3.4640854
MonotonicityDecreasing
2023-12-12T12:20:46.311918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.01 21
 
13.9%
0.0 18
 
11.9%
0.03 12
 
7.9%
0.02 10
 
6.6%
0.04 6
 
4.0%
0.05 5
 
3.3%
0.06 4
 
2.6%
0.12 4
 
2.6%
0.08 3
 
2.0%
0.09 3
 
2.0%
Other values (52) 65
43.0%
ValueCountFrequency (%)
0.0 18
11.9%
0.01 21
13.9%
0.02 10
6.6%
0.03 12
7.9%
0.04 6
 
4.0%
0.05 5
 
3.3%
0.06 4
 
2.6%
0.07 3
 
2.0%
0.08 3
 
2.0%
0.09 3
 
2.0%
ValueCountFrequency (%)
17.6 1
0.7%
9.02 1
0.7%
6.75 1
0.7%
5.89 1
0.7%
3.98 1
0.7%
3.23 1
0.7%
3.09 1
0.7%
3.03 1
0.7%
2.93 1
0.7%
2.92 1
0.7%

Interactions

2023-12-12T12:20:43.480364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:20:42.409507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:20:42.803575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:20:43.124789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:20:43.585757image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:20:42.505744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:20:42.887479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:20:43.215586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:20:43.680282image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:20:42.602450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:20:42.963467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:20:43.298016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:20:43.772867image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:20:42.698287image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:20:43.043708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:20:43.394736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T12:20:46.447145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번업종코드총 사용금액사용비율
순번1.0000.4720.3110.5950.596
업종0.4721.0001.0000.0000.000
코드0.3111.0001.0000.0000.000
총 사용금액0.5950.0000.0001.0001.000
사용비율0.5960.0000.0001.0001.000
2023-12-12T12:20:46.564379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번코드총 사용금액사용비율업종
순번1.000-0.031-1.000-0.9970.206
코드-0.0311.0000.0310.0390.899
총 사용금액-1.0000.0311.0000.9970.000
사용비율-0.9970.0390.9971.0000.000
업종0.2060.8990.0000.0001.000

Missing values

2023-12-12T12:20:43.883654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T12:20:43.986031image/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

순번업종코드세부업종총 사용금액사용비율
01일반/휴게 음식3001일반한식1821737407917.6
12학원7104보습/문리계학원93393363259.02
23일반유통6101편의점69913921366.75
34학원7103예.체능계학원60974849815.89
45의원8101의원41246244813.98
56약국8202약국33406211523.23
67학원7101외국어학원32036614073.09
78일반/휴게 음식3004서양음식31374153623.03
89의원8103치과의원30331383642.93
910미용/위생8402미용원30273561012.92
순번업종코드세부업종총 사용금액사용비율
141142상품권6601상품권24512900.0
142143신변잡화4207기념품점20955000.0
143144주방용품2203정수기18290000.0
144145숙박업1002일반호텔17800000.0
145146관광1201관광여행사16297000.0
146147문화/취미5201골동품점13612000.0
147148문화/취미5203화방/표구점8495000.0
148149전자상거래6501인터넷PG4015000.0
149150비영리유통6403공공기관 직영점1880000.0
150151레저/문화 용품5002총포류판매점270000.0