Overview

Dataset statistics

Number of variables12
Number of observations99
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory9.9 KiB
Average record size in memory102.3 B

Variable types

Categorical9
Numeric3

Dataset

DescriptionSample
Author(주)제로투원파트너스
URLhttps://www.bigdata-telecom.kr/invoke/SOKBP2603/?goodsCode=ZTO010BSICGIMASSAGER

Alerts

MT has constant value ""Constant
안마기기/마사지기 has constant value ""Constant
전체 has constant value ""Constant
전체.1 has constant value ""Constant
바디프랜드 has constant value ""Constant
경기도 is highly overall correlated with 전체.2High correlation
전체.2 is highly overall correlated with 경기도High correlation

Reproduction

Analysis started2023-12-10 06:43:39.783181
Analysis finished2023-12-10 06:43:42.203488
Duration2.42 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

MT
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size924.0 B
MT
99 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowMT
2nd rowMT
3rd rowMT
4th rowMT
5th rowMT

Common Values

ValueCountFrequency (%)
MT 99
100.0%

Length

2023-12-10T15:43:42.303412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:43:42.442328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
mt 99
100.0%

201803
Categorical

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size924.0 B
201803
56 
201801
43 

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row201803
2nd row201803
3rd row201803
4th row201803
5th row201803

Common Values

ValueCountFrequency (%)
201803 56
56.6%
201801 43
43.4%

Length

2023-12-10T15:43:42.628546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:43:42.816937image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
201803 56
56.6%
201801 43
43.4%

83
Real number (ℝ)

Distinct67
Distinct (%)67.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean113.62626
Minimum23
Maximum356
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1023.0 B
2023-12-10T15:43:43.032670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum23
5-th percentile49.3
Q185
median100
Q3136.5
95-th percentile227.9
Maximum356
Range333
Interquartile range (IQR)51.5

Descriptive statistics

Standard deviation55.641818
Coefficient of variation (CV)0.48969153
Kurtosis3.6411218
Mean113.62626
Median Absolute Deviation (MAD)27
Skewness1.5360111
Sum11249
Variance3096.012
MonotonicityNot monotonic
2023-12-10T15:43:43.296912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
100 19
 
19.2%
61 4
 
4.0%
148 3
 
3.0%
90 2
 
2.0%
120 2
 
2.0%
132 2
 
2.0%
81 2
 
2.0%
62 2
 
2.0%
109 2
 
2.0%
43 2
 
2.0%
Other values (57) 59
59.6%
ValueCountFrequency (%)
23 1
1.0%
29 1
1.0%
37 1
1.0%
43 2
2.0%
50 2
2.0%
51 1
1.0%
53 2
2.0%
56 1
1.0%
58 1
1.0%
59 1
1.0%
ValueCountFrequency (%)
356 1
1.0%
269 1
1.0%
257 1
1.0%
254 1
1.0%
236 1
1.0%
227 1
1.0%
225 1
1.0%
205 1
1.0%
198 1
1.0%
178 1
1.0%

100
Real number (ℝ)

Distinct20
Distinct (%)20.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean94.565657
Minimum24
Maximum100
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1023.0 B
2023-12-10T15:43:43.528068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum24
5-th percentile61.8
Q1100
median100
Q3100
95-th percentile100
Maximum100
Range76
Interquartile range (IQR)0

Descriptive statistics

Standard deviation14.928511
Coefficient of variation (CV)0.15786398
Kurtosis10.018368
Mean94.565657
Median Absolute Deviation (MAD)0
Skewness-3.1936662
Sum9362
Variance222.86044
MonotonicityNot monotonic
2023-12-10T15:43:43.765414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
100 75
75.8%
99 4
 
4.0%
96 2
 
2.0%
97 2
 
2.0%
90 1
 
1.0%
65 1
 
1.0%
98 1
 
1.0%
67 1
 
1.0%
94 1
 
1.0%
51 1
 
1.0%
Other values (10) 10
 
10.1%
ValueCountFrequency (%)
24 1
1.0%
29 1
1.0%
46 1
1.0%
48 1
1.0%
51 1
1.0%
63 1
1.0%
65 1
1.0%
67 1
1.0%
70 1
1.0%
78 1
1.0%
ValueCountFrequency (%)
100 75
75.8%
99 4
 
4.0%
98 1
 
1.0%
97 2
 
2.0%
96 2
 
2.0%
94 1
 
1.0%
90 1
 
1.0%
89 1
 
1.0%
88 1
 
1.0%
80 1
 
1.0%

안마기기/마사지기
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size924.0 B
안마기기/마사지기
99 

Length

Max length9
Median length9
Mean length9
Min length9

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row안마기기/마사지기
2nd row안마기기/마사지기
3rd row안마기기/마사지기
4th row안마기기/마사지기
5th row안마기기/마사지기

Common Values

ValueCountFrequency (%)
안마기기/마사지기 99
100.0%

Length

2023-12-10T15:43:44.004081image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:43:44.212175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
안마기기/마사지기 99
100.0%

전체
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size924.0 B
전체
99 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row전체
2nd row전체
3rd row전체
4th row전체
5th row전체

Common Values

ValueCountFrequency (%)
전체 99
100.0%

Length

2023-12-10T15:43:44.375902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:43:44.519499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
전체 99
100.0%

전체.1
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size924.0 B
전체
99 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row전체
2nd row전체
3rd row전체
4th row전체
5th row전체

Common Values

ValueCountFrequency (%)
전체 99
100.0%

Length

2023-12-10T15:43:44.661986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:43:44.796855image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
전체 99
100.0%

2
Categorical

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size924.0 B
2
74 
1
25 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2
2nd row2
3rd row2
4th row2
5th row2

Common Values

ValueCountFrequency (%)
2 74
74.7%
1 25
 
25.3%

Length

2023-12-10T15:43:44.972672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:43:45.141185image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 74
74.7%
1 25
 
25.3%

20
Real number (ℝ)

Distinct6
Distinct (%)6.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean42.828283
Minimum20
Maximum70
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1023.0 B
2023-12-10T15:43:45.297487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20
5-th percentile29
Q130
median40
Q350
95-th percentile60
Maximum70
Range50
Interquartile range (IQR)20

Descriptive statistics

Standard deviation12.040781
Coefficient of variation (CV)0.28114089
Kurtosis-0.74344286
Mean42.828283
Median Absolute Deviation (MAD)10
Skewness0.11458526
Sum4240
Variance144.98042
MonotonicityNot monotonic
2023-12-10T15:43:45.498554image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
40 28
28.3%
30 24
24.2%
50 24
24.2%
60 16
16.2%
20 5
 
5.1%
70 2
 
2.0%
ValueCountFrequency (%)
20 5
 
5.1%
30 24
24.2%
40 28
28.3%
50 24
24.2%
60 16
16.2%
70 2
 
2.0%
ValueCountFrequency (%)
70 2
 
2.0%
60 16
16.2%
50 24
24.2%
40 28
28.3%
30 24
24.2%
20 5
 
5.1%

경기도
Categorical

HIGH CORRELATION 

Distinct11
Distinct (%)11.1%
Missing0
Missing (%)0.0%
Memory size924.0 B
경기도
21 
부산광역시
17 
전라북도
16 
서울특별시
9 
인천광역시
8 
Other values (6)
28 

Length

Max length5
Median length4
Mean length4.2222222
Min length3

Unique

Unique2 ?
Unique (%)2.0%

Sample

1st row경상남도
2nd row부산광역시
3rd row부산광역시
4th row인천광역시
5th row경기도

Common Values

ValueCountFrequency (%)
경기도 21
21.2%
부산광역시 17
17.2%
전라북도 16
16.2%
서울특별시 9
9.1%
인천광역시 8
 
8.1%
대구광역시 8
 
8.1%
경상남도 6
 
6.1%
전라남도 6
 
6.1%
충청북도 6
 
6.1%
대전광역시 1
 
1.0%

Length

2023-12-10T15:43:45.722555image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
경기도 21
21.2%
부산광역시 17
17.2%
전라북도 16
16.2%
서울특별시 9
9.1%
인천광역시 8
 
8.1%
대구광역시 8
 
8.1%
경상남도 6
 
6.1%
전라남도 6
 
6.1%
충청북도 6
 
6.1%
대전광역시 1
 
1.0%

전체.2
Categorical

HIGH CORRELATION 

Distinct24
Distinct (%)24.2%
Missing0
Missing (%)0.0%
Memory size924.0 B
전체
51 
익산시
6 
청주시
6 
김해시
 
4
사상구
 
4
Other values (19)
28 

Length

Max length4
Median length2
Mean length2.4646465
Min length2

Unique

Unique13 ?
Unique (%)13.1%

Sample

1st row거제시
2nd row전체
3rd row동래구
4th row전체
5th row전체

Common Values

ValueCountFrequency (%)
전체 51
51.5%
익산시 6
 
6.1%
청주시 6
 
6.1%
김해시 4
 
4.0%
사상구 4
 
4.0%
노원구 3
 
3.0%
중구 3
 
3.0%
부천시 3
 
3.0%
평택시 2
 
2.0%
강서구 2
 
2.0%
Other values (14) 15
 
15.2%

Length

2023-12-10T15:43:46.318965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
전체 51
51.5%
청주시 6
 
6.1%
익산시 6
 
6.1%
김해시 4
 
4.0%
사상구 4
 
4.0%
노원구 3
 
3.0%
중구 3
 
3.0%
부천시 3
 
3.0%
송파구 2
 
2.0%
평택시 2
 
2.0%
Other values (14) 15
 
15.2%

바디프랜드
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size924.0 B
바디프랜드
99 

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row바디프랜드
2nd row바디프랜드
3rd row바디프랜드
4th row바디프랜드
5th row바디프랜드

Common Values

ValueCountFrequency (%)
바디프랜드 99
100.0%

Length

2023-12-10T15:43:46.498845image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:43:46.628237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
바디프랜드 99
100.0%

Interactions

2023-12-10T15:43:41.202146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:43:40.338402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:43:40.753283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:43:41.379008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:43:40.471461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:43:40.887910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:43:41.560491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:43:40.616198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:43:41.059593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T15:43:46.728980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
20180383100220경기도전체.2
2018031.0000.0000.0000.2770.1210.0000.000
830.0001.0000.5110.2010.0000.0000.000
1000.0000.5111.0000.3280.0000.0000.000
20.2770.2010.3281.0000.0000.0000.000
200.1210.0000.0000.0001.0000.0000.000
경기도0.0000.0000.0000.0000.0001.0000.920
전체.20.0000.0000.0000.0000.0000.9201.000
2023-12-10T15:43:46.896018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
전체.2경기도2201803
전체.21.0000.5990.0000.000
경기도0.5991.0000.0000.000
20.0000.0001.0000.179
2018030.0000.0000.1791.000
2023-12-10T15:43:47.080491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
83100202018032경기도전체.2
831.000-0.013-0.0690.0000.1910.0000.000
100-0.0131.000-0.0080.0000.2370.0000.000
20-0.069-0.0081.0000.0820.0000.0000.000
2018030.0000.0000.0821.0000.1790.0000.000
20.1910.2370.0000.1791.0000.0000.000
경기도0.0000.0000.0000.0000.0001.0000.599
전체.20.0000.0000.0000.0000.0000.5991.000

Missing values

2023-12-10T15:43:41.796255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T15:43:42.105415image/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

MT20180383100안마기기/마사지기전체전체.1220경기도전체.2바디프랜드
0MT201803100100안마기기/마사지기전체전체220경상남도거제시바디프랜드
1MT2018034324안마기기/마사지기전체전체230부산광역시전체바디프랜드
2MT201803100100안마기기/마사지기전체전체230부산광역시동래구바디프랜드
3MT201803152100안마기기/마사지기전체전체230인천광역시전체바디프랜드
4MT2018035046안마기기/마사지기전체전체230경기도전체바디프랜드
5MT20180384100안마기기/마사지기전체전체230경기도평택시바디프랜드
6MT201803269100안마기기/마사지기전체전체230전라북도전체바디프랜드
7MT201803100100안마기기/마사지기전체전체230전라북도익산시바디프랜드
8MT20180393100안마기기/마사지기전체전체240서울특별시노원구바디프랜드
9MT201803159100안마기기/마사지기전체전체240부산광역시전체바디프랜드
MT20180383100안마기기/마사지기전체전체.1220경기도전체.2바디프랜드
89MT20180114096안마기기/마사지기전체전체260경기도전체바디프랜드
90MT20180153100안마기기/마사지기전체전체260전라북도전체바디프랜드
91MT20180190100안마기기/마사지기전체전체260전라북도익산시바디프랜드
92MT201801100100안마기기/마사지기전체전체270서울특별시노원구바디프랜드
93MT201801145100안마기기/마사지기전체전체120전라북도전체바디프랜드
94MT201801100100안마기기/마사지기전체전체120전라북도익산시바디프랜드
95MT201801155100안마기기/마사지기전체전체130부산광역시전체바디프랜드
96MT20180161100안마기기/마사지기전체전체130경기도전체바디프랜드
97MT201801198100안마기기/마사지기전체전체130전라남도전체바디프랜드
98MT201801100100안마기기/마사지기전체전체140서울특별시노원구바디프랜드