Overview

Dataset statistics

Number of variables8
Number of observations43
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.0 KiB
Average record size in memory72.1 B

Variable types

Text2
Numeric4
Categorical1
DateTime1

Dataset

Description세종 특별 자치시에 소재한 음식점과 피씨방 등 서비스 업종 요금 현황에 관련되어 있는 데이터가 담겨있는 엑셀 파일입니다.
Author세종특별자치시
URLhttps://www.data.go.kr/data/15045474/fileData.do

Alerts

등록기준일 has constant value ""Constant
조치원(23년2월) is highly overall correlated with 종촌동(23년2월) and 2 other fieldsHigh correlation
종촌동(23년2월) is highly overall correlated with 조치원(23년2월) and 2 other fieldsHigh correlation
평 균(A) is highly overall correlated with 조치원(23년2월) and 2 other fieldsHigh correlation
2023년1월가격(B) is highly overall correlated with 조치원(23년2월) and 2 other fieldsHigh correlation
증감(A-B) is highly imbalanced (76.2%)Imbalance
품 목 has unique valuesUnique
조치원(23년2월) has 2 (4.7%) zerosZeros

Reproduction

Analysis started2023-12-12 20:59:37.362596
Analysis finished2023-12-12 20:59:39.286649
Duration1.92 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

품 목
Text

UNIQUE 

Distinct43
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size476.0 B
2023-12-13T05:59:39.442310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length7
Mean length4
Min length2

Characters and Unicode

Total characters172
Distinct characters95
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

Unique43 ?
Unique (%)100.0%

Sample

1st row설렁탕
2nd row냉면
3rd row비빔밥
4th row갈비탕
5th row삼계탕
ValueCountFrequency (%)
설렁탕 1
 
2.3%
커피 1
 
2.3%
생맥주 1
 
2.3%
세탁료 1
 
2.3%
공동주택관리비 1
 
2.3%
택배이용료 1
 
2.3%
수영장이용료 1
 
2.3%
볼링장이용료 1
 
2.3%
골프연습장이용료 1
 
2.3%
당구장이용료 1
 
2.3%
Other values (33) 33
76.7%
2023-12-13T05:59:39.840265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
료 17
 
9.9%
용 10
 
5.8%
이 9
 
5.2%
장 6
 
3.5%
탕 4
 
2.3%
비 4
 
2.3%
면 3
 
1.7%
관 3
 
1.7%
밥 3
 
1.7%
수 3
 
1.7%
Other values (85) 110
64.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 166
96.5%
Open Punctuation 2
 
1.2%
Close Punctuation 2
 
1.2%
Uppercase Letter 2
 
1.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
료 17
 
10.2%
용 10
 
6.0%
이 9
 
5.4%
장 6
 
3.6%
탕 4
 
2.4%
비 4
 
2.4%
면 3
 
1.8%
관 3
 
1.8%
밥 3
 
1.8%
수 3
 
1.8%
Other values (81) 104
62.7%
Uppercase Letter
ValueCountFrequency (%)
C 1
50.0%
P 1
50.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 166
96.5%
Common 4
 
2.3%
Latin 2
 
1.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
료 17
 
10.2%
용 10
 
6.0%
이 9
 
5.4%
장 6
 
3.6%
탕 4
 
2.4%
비 4
 
2.4%
면 3
 
1.8%
관 3
 
1.8%
밥 3
 
1.8%
수 3
 
1.8%
Other values (81) 104
62.7%
Common
ValueCountFrequency (%)
( 2
50.0%
) 2
50.0%
Latin
ValueCountFrequency (%)
C 1
50.0%
P 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 166
96.5%
ASCII 6
 
3.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
료 17
 
10.2%
용 10
 
6.0%
이 9
 
5.4%
장 6
 
3.6%
탕 4
 
2.4%
비 4
 
2.4%
면 3
 
1.8%
관 3
 
1.8%
밥 3
 
1.8%
수 3
 
1.8%
Other values (81) 104
62.7%
ASCII
ValueCountFrequency (%)
( 2
33.3%
) 2
33.3%
C 1
16.7%
P 1
16.7%

규 격 및 단 위
Text

Distinct30
Distinct (%)69.8%
Missing0
Missing (%)0.0%
Memory size476.0 B
2023-12-13T05:59:40.066270image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length6.9767442
Min length1

Characters and Unicode

Total characters300
Distinct characters85
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique24 ?
Unique (%)55.8%

Sample

1st row1그릇(대중식당)
2nd row1그릇(대중식당)
3rd row1그릇(대중식당)
4th row1그릇(대중식당)
5th row1그릇(대중식당)
ValueCountFrequency (%)
1그릇(대중식당 5
 
11.1%
1인분(200g 4
 
8.9%
성인1회 4
 
8.9%
1그릇(중국집 2
 
4.4%
1그릇(분식집 2
 
4.4%
1인분 2
 
4.4%
20kg 1
 
2.2%
1시간(쿠션당구대일반 1
 
2.2%
1시간(일반실저녁 1
 
2.2%
1시간 1
 
2.2%
Other values (22) 22
48.9%
2023-12-13T05:59:40.414589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 39
 
13.0%
( 27
 
9.0%
) 27
 
9.0%
인 15
 
5.0%
0 11
 
3.7%
분 10
 
3.3%
릇 9
 
3.0%
식 9
 
3.0%
그 9
 
3.0%
대 7
 
2.3%
Other values (75) 137
45.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 173
57.7%
Decimal Number 62
 
20.7%
Open Punctuation 27
 
9.0%
Close Punctuation 27
 
9.0%
Lowercase Letter 9
 
3.0%
Space Separator 2
 
0.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
인 15
 
8.7%
분 10
 
5.8%
릇 9
 
5.2%
식 9
 
5.2%
그 9
 
5.2%
대 7
 
4.0%
중 7
 
4.0%
일 6
 
3.5%
당 6
 
3.5%
집 6
 
3.5%
Other values (62) 89
51.4%
Decimal Number
ValueCountFrequency (%)
1 39
62.9%
0 11
 
17.7%
2 7
 
11.3%
5 2
 
3.2%
3 2
 
3.2%
9 1
 
1.6%
Lowercase Letter
ValueCountFrequency (%)
g 5
55.6%
c 2
 
22.2%
k 1
 
11.1%
x 1
 
11.1%
Open Punctuation
ValueCountFrequency (%)
( 27
100.0%
Close Punctuation
ValueCountFrequency (%)
) 27
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 173
57.7%
Common 118
39.3%
Latin 9
 
3.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
인 15
 
8.7%
분 10
 
5.8%
릇 9
 
5.2%
식 9
 
5.2%
그 9
 
5.2%
대 7
 
4.0%
중 7
 
4.0%
일 6
 
3.5%
당 6
 
3.5%
집 6
 
3.5%
Other values (62) 89
51.4%
Common
ValueCountFrequency (%)
1 39
33.1%
( 27
22.9%
) 27
22.9%
0 11
 
9.3%
2 7
 
5.9%
2
 
1.7%
5 2
 
1.7%
3 2
 
1.7%
9 1
 
0.8%
Latin
ValueCountFrequency (%)
g 5
55.6%
c 2
 
22.2%
k 1
 
11.1%
x 1
 
11.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 173
57.7%
ASCII 127
42.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 39
30.7%
( 27
21.3%
) 27
21.3%
0 11
 
8.7%
2 7
 
5.5%
g 5
 
3.9%
2
 
1.6%
c 2
 
1.6%
5 2
 
1.6%
3 2
 
1.6%
Other values (3) 3
 
2.4%
Hangul
ValueCountFrequency (%)
인 15
 
8.7%
분 10
 
5.8%
릇 9
 
5.2%
식 9
 
5.2%
그 9
 
5.2%
대 7
 
4.0%
중 7
 
4.0%
일 6
 
3.5%
당 6
 
3.5%
집 6
 
3.5%
Other values (62) 89
51.4%

조치원(23년2월)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct23
Distinct (%)53.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20369.767
Minimum0
Maximum260000
Zeros2
Zeros (%)4.7%
Negative0
Negative (%)0.0%
Memory size519.0 B
2023-12-13T05:59:40.546381image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile550
Q14000
median8000
Q312450
95-th percentile48500
Maximum260000
Range260000
Interquartile range (IQR)8450

Descriptive statistics

Standard deviation46912.54
Coefficient of variation (CV)2.3030474
Kurtosis19.653391
Mean20369.767
Median Absolute Deviation (MAD)4000
Skewness4.3893821
Sum875900
Variance2.2007864 × 109
MonotonicityNot monotonic
2023-12-13T05:59:40.678072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
12000 7
16.3%
8000 6
14.0%
4000 4
 
9.3%
7000 4
 
9.3%
0 2
 
4.7%
15000 2
 
4.7%
3000 2
 
4.7%
260000 1
 
2.3%
50000 1
 
2.3%
500 1
 
2.3%
Other values (13) 13
30.2%
ValueCountFrequency (%)
0 2
 
4.7%
500 1
 
2.3%
1000 1
 
2.3%
2000 1
 
2.3%
2500 1
 
2.3%
3000 2
 
4.7%
4000 4
9.3%
5000 1
 
2.3%
7000 4
9.3%
8000 6
14.0%
ValueCountFrequency (%)
260000 1
2.3%
185000 1
2.3%
50000 1
2.3%
35000 1
2.3%
29000 1
2.3%
28000 1
2.3%
20000 1
2.3%
15000 2
4.7%
14000 1
2.3%
12900 1
2.3%

종촌동(23년2월)
Real number (ℝ)

HIGH CORRELATION 

Distinct36
Distinct (%)83.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20642.791
Minimum500
Maximum189100
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size519.0 B
2023-12-13T05:59:40.791538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum500
5-th percentile2080
Q15000
median10800
Q316000
95-th percentile60900
Maximum189100
Range188600
Interquartile range (IQR)11000

Descriptive statistics

Standard deviation35770.028
Coefficient of variation (CV)1.7328097
Kurtosis14.41842
Mean20642.791
Median Absolute Deviation (MAD)5800
Skewness3.6932109
Sum887640
Variance1.2794949 × 109
MonotonicityNot monotonic
2023-12-13T05:59:40.940495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=36)
ValueCountFrequency (%)
8000 2
 
4.7%
7000 2
 
4.7%
13000 2
 
4.7%
9000 2
 
4.7%
5000 2
 
4.7%
12000 2
 
4.7%
4900 2
 
4.7%
1300 1
 
2.3%
4000 1
 
2.3%
145000 1
 
2.3%
Other values (26) 26
60.5%
ValueCountFrequency (%)
500 1
2.3%
1300 1
2.3%
2000 1
2.3%
2800 1
2.3%
3000 1
2.3%
3200 1
2.3%
3500 1
2.3%
4000 1
2.3%
4900 2
4.7%
5000 2
4.7%
ValueCountFrequency (%)
189100 1
2.3%
145000 1
2.3%
61000 1
2.3%
60000 1
2.3%
50000 1
2.3%
30000 1
2.3%
23000 1
2.3%
22000 1
2.3%
19000 1
2.3%
18000 1
2.3%

평 균(A)
Real number (ℝ)

HIGH CORRELATION 

Distinct40
Distinct (%)93.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean21378.372
Minimum500
Maximum224550
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size519.0 B
2023-12-13T05:59:41.103458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum500
5-th percentile2500
Q15725
median10400
Q316000
95-th percentile59000
Maximum224550
Range224050
Interquartile range (IQR)10275

Descriptive statistics

Standard deviation41236.19
Coefficient of variation (CV)1.9288742
Kurtosis17.050501
Mean21378.372
Median Absolute Deviation (MAD)5400
Skewness4.0410415
Sum919270
Variance1.7004233 × 109
MonotonicityNot monotonic
2023-12-13T05:59:41.541619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=40)
ValueCountFrequency (%)
8000 2
 
4.7%
8500 2
 
4.7%
2500 2
 
4.7%
12500 1
 
2.3%
1150 1
 
2.3%
6450 1
 
2.3%
224550 1
 
2.3%
4500 1
 
2.3%
4000 1
 
2.3%
165000 1
 
2.3%
Other values (30) 30
69.8%
ValueCountFrequency (%)
500 1
2.3%
1150 1
2.3%
2500 2
4.7%
2850 1
2.3%
2900 1
2.3%
3750 1
2.3%
4000 1
2.3%
4450 1
2.3%
4500 1
2.3%
5000 1
2.3%
ValueCountFrequency (%)
224550 1
2.3%
165000 1
2.3%
60000 1
2.3%
50000 1
2.3%
48000 1
2.3%
26000 1
2.3%
22500 1
2.3%
20500 1
2.3%
18500 1
2.3%
17000 1
2.3%

2023년1월가격(B)
Real number (ℝ)

HIGH CORRELATION 

Distinct40
Distinct (%)93.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean21215.581
Minimum500
Maximum224550
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size519.0 B
2023-12-13T05:59:41.691727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum500
5-th percentile2500
Q15725
median10400
Q314860
95-th percentile59000
Maximum224550
Range224050
Interquartile range (IQR)9135

Descriptive statistics

Standard deviation41251.764
Coefficient of variation (CV)1.9444088
Kurtosis17.090101
Mean21215.581
Median Absolute Deviation (MAD)5100
Skewness4.0487647
Sum912270
Variance1.701708 × 109
MonotonicityNot monotonic
2023-12-13T05:59:41.820491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=40)
ValueCountFrequency (%)
8000 2
 
4.7%
8500 2
 
4.7%
2500 2
 
4.7%
12500 1
 
2.3%
1150 1
 
2.3%
6450 1
 
2.3%
224550 1
 
2.3%
4500 1
 
2.3%
4000 1
 
2.3%
165000 1
 
2.3%
Other values (30) 30
69.8%
ValueCountFrequency (%)
500 1
2.3%
1150 1
2.3%
2500 2
4.7%
2850 1
2.3%
2900 1
2.3%
3750 1
2.3%
4000 1
2.3%
4450 1
2.3%
4500 1
2.3%
5000 1
2.3%
ValueCountFrequency (%)
224550 1
2.3%
165000 1
2.3%
60000 1
2.3%
50000 1
2.3%
48000 1
2.3%
26000 1
2.3%
22500 1
2.3%
18500 1
2.3%
17000 1
2.3%
16500 1
2.3%

증감(A-B)
Categorical

IMBALANCE 

Distinct4
Distinct (%)9.3%
Missing0
Missing (%)0.0%
Memory size476.0 B
0
40 
1000
 
1
7000
 
1
-1000
 
1

Length

Max length5
Median length1
Mean length1.2325581
Min length1

Unique

Unique3 ?
Unique (%)7.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row1000

Common Values

ValueCountFrequency (%)
0 40
93.0%
1000 1
 
2.3%
7000 1
 
2.3%
-1000 1
 
2.3%

Length

2023-12-13T05:59:41.949826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T05:59:42.118515image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 40
93.0%
1000 2
 
4.7%
7000 1
 
2.3%

등록기준일
Date

CONSTANT 

Distinct1
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Memory size476.0 B
Minimum2023-03-07 00:00:00
Maximum2023-03-07 00:00:00
2023-12-13T05:59:42.222316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:59:42.300251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-13T05:59:38.751025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:59:37.661266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:59:38.067065image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:59:38.417622image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:59:38.826839image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:59:37.765759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:59:38.179415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:59:38.497763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:59:38.913942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:59:37.871693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:59:38.265106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:59:38.597815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:59:38.996300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:59:37.950530image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:59:38.339887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:59:38.677868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T05:59:42.369756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
품 목규 격 및 단 위조치원(23년2월)종촌동(23년2월)평 균(A)2023년1월가격(B)증감(A-B)
품 목1.0001.0001.0001.0001.0001.0001.000
규 격 및 단 위1.0001.0000.9600.9740.9770.9770.000
조치원(23년2월)1.0000.9601.0000.9670.9070.9070.253
종촌동(23년2월)1.0000.9740.9671.0000.9300.9300.000
평 균(A)1.0000.9770.9070.9301.0001.0000.000
2023년1월가격(B)1.0000.9770.9070.9301.0001.0000.000
증감(A-B)1.0000.0000.2530.0000.0000.0001.000
2023-12-13T05:59:42.476539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
조치원(23년2월)종촌동(23년2월)평 균(A)2023년1월가격(B)증감(A-B)
조치원(23년2월)1.0000.7490.7840.7790.092
종촌동(23년2월)0.7491.0000.9860.9900.000
평 균(A)0.7840.9861.0000.9970.000
2023년1월가격(B)0.7790.9900.9971.0000.000
증감(A-B)0.0920.0000.0000.0001.000

Missing values

2023-12-13T05:59:39.101080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T05:59:39.237094image/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

품 목규 격 및 단 위조치원(23년2월)종촌동(23년2월)평 균(A)2023년1월가격(B)증감(A-B)등록기준일
0설렁탕1그릇(대중식당)800080008000800002023-03-07
1냉면1그릇(대중식당)7000110009000900002023-03-07
2비빔밥1그릇(대중식당)700070007000700002023-03-07
3갈비탕1그릇(대중식당)1200013000125001250002023-03-07
4삼계탕1그릇(대중식당)015000150001400010002023-03-07
5김치찌개백반1인분800090008500850002023-03-07
6된장찌개백반1인분800090008500850002023-03-07
7불고기1인분(200g)1200019000155001550002023-03-07
8등심1인분(200g)3500061000480004800002023-03-07
9돼지갈비1인분(200g)2800013000205001350070002023-03-07
품 목규 격 및 단 위조치원(23년2월)종촌동(23년2월)평 균(A)2023년1월가격(B)증감(A-B)등록기준일
33PC방이용료1시간100013001150115002023-03-07
34영화관람료1회(일반)1200014000130001300002023-03-07
35사진촬영료증명판1500018000165001650002023-03-07
36사진인화료3x5(현상인화료포함)50050050050002023-03-07
37숙박료(호텔)1박(관광호텔2급2종)060000600006000002023-03-07
38숙박료(여관)1박5000050000500005000002023-03-07
39이용료성인1회1200012000120001200002023-03-07
40미용료커트1200022000170001700002023-03-07
41목욕료성인1회800080008000800002023-03-07
42찜질방이용료성인1회1200010000110001100002023-03-07