Overview

Dataset statistics

Number of variables13
Number of observations99
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory10.9 KiB
Average record size in memory112.3 B

Variable types

Categorical9
Numeric4

Dataset

DescriptionSample
Author(주)제로투원파트너스
URLhttps://www.bigdata-telecom.kr/invoke/SOKBP2603/?goodsCode=ZTO011TOTALCGIDAIRY

Alerts

MT has constant value ""Constant
201901 has constant value ""Constant
유제품 has constant value ""Constant
99 is highly overall correlated with 전체 and 2 other fieldsHigh correlation
전체.1 is highly overall correlated with 79 and 3 other fieldsHigh correlation
2 is highly overall correlated with 79 and 3 other fieldsHigh correlation
전체 is highly overall correlated with 79 and 3 other fieldsHigh correlation
218 is highly overall correlated with 218.1High correlation
79 is highly overall correlated with 전체 and 2 other fieldsHigh correlation
218.1 is highly overall correlated with 218High correlation
인천광역시 is highly overall correlated with 연수구High correlation
연수구 is highly overall correlated with 인천광역시High correlation

Reproduction

Analysis started2023-12-10 06:36:24.113765
Analysis finished2023-12-10 06:36:28.876925
Duration4.76 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

2023-12-10T15:36:28.972365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:36:29.108088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
mt 99
100.0%

201901
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size924.0 B
201901
99 

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row201901
2nd row201901
3rd row201901
4th row201901
5th row201901

Common Values

ValueCountFrequency (%)
201901 99
100.0%

Length

2023-12-10T15:36:29.262003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:36:29.451647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
201901 99
100.0%

218
Real number (ℝ)

HIGH CORRELATION 

Distinct80
Distinct (%)80.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean148.34343
Minimum16
Maximum1184
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1023.0 B
2023-12-10T15:36:29.630978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum16
5-th percentile33.8
Q191
median118
Q3156
95-th percentile341.8
Maximum1184
Range1168
Interquartile range (IQR)65

Descriptive statistics

Standard deviation141.29497
Coefficient of variation (CV)0.9524855
Kurtosis31.081405
Mean148.34343
Median Absolute Deviation (MAD)31
Skewness4.8624794
Sum14686
Variance19964.269
MonotonicityNot monotonic
2023-12-10T15:36:29.843965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
102 4
 
4.0%
126 3
 
3.0%
118 3
 
3.0%
84 3
 
3.0%
106 3
 
3.0%
87 2
 
2.0%
103 2
 
2.0%
92 2
 
2.0%
146 2
 
2.0%
113 2
 
2.0%
Other values (70) 73
73.7%
ValueCountFrequency (%)
16 1
1.0%
19 1
1.0%
20 1
1.0%
29 1
1.0%
32 1
1.0%
34 1
1.0%
42 1
1.0%
53 1
1.0%
54 1
1.0%
59 1
1.0%
ValueCountFrequency (%)
1184 1
1.0%
691 1
1.0%
435 1
1.0%
399 1
1.0%
376 1
1.0%
338 1
1.0%
320 1
1.0%
266 1
1.0%
265 1
1.0%
251 1
1.0%

79
Real number (ℝ)

HIGH CORRELATION 

Distinct77
Distinct (%)77.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean137.92929
Minimum21
Maximum883
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1023.0 B
2023-12-10T15:36:30.073983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum21
5-th percentile47
Q175
median92
Q3157
95-th percentile360.7
Maximum883
Range862
Interquartile range (IQR)82

Descriptive statistics

Standard deviation122.47301
Coefficient of variation (CV)0.88794052
Kurtosis14.650655
Mean137.92929
Median Absolute Deviation (MAD)27
Skewness3.2841316
Sum13655
Variance14999.638
MonotonicityNot monotonic
2023-12-10T15:36:30.321068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
75 4
 
4.0%
80 4
 
4.0%
62 3
 
3.0%
85 3
 
3.0%
107 3
 
3.0%
81 3
 
3.0%
165 2
 
2.0%
99 2
 
2.0%
47 2
 
2.0%
66 2
 
2.0%
Other values (67) 71
71.7%
ValueCountFrequency (%)
21 1
 
1.0%
22 1
 
1.0%
43 1
 
1.0%
44 1
 
1.0%
47 2
2.0%
51 1
 
1.0%
54 1
 
1.0%
60 1
 
1.0%
62 3
3.0%
63 1
 
1.0%
ValueCountFrequency (%)
883 1
1.0%
521 1
1.0%
489 1
1.0%
472 1
1.0%
385 1
1.0%
358 1
1.0%
325 1
1.0%
283 1
1.0%
280 1
1.0%
275 1
1.0%

218.1
Real number (ℝ)

HIGH CORRELATION 

Distinct80
Distinct (%)80.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean148.34343
Minimum16
Maximum1184
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1023.0 B
2023-12-10T15:36:30.537701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum16
5-th percentile33.8
Q191
median118
Q3156
95-th percentile341.8
Maximum1184
Range1168
Interquartile range (IQR)65

Descriptive statistics

Standard deviation141.29497
Coefficient of variation (CV)0.9524855
Kurtosis31.081405
Mean148.34343
Median Absolute Deviation (MAD)31
Skewness4.8624794
Sum14686
Variance19964.269
MonotonicityNot monotonic
2023-12-10T15:36:30.703569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
102 4
 
4.0%
126 3
 
3.0%
118 3
 
3.0%
84 3
 
3.0%
106 3
 
3.0%
87 2
 
2.0%
103 2
 
2.0%
92 2
 
2.0%
146 2
 
2.0%
113 2
 
2.0%
Other values (70) 73
73.7%
ValueCountFrequency (%)
16 1
1.0%
19 1
1.0%
20 1
1.0%
29 1
1.0%
32 1
1.0%
34 1
1.0%
42 1
1.0%
53 1
1.0%
54 1
1.0%
59 1
1.0%
ValueCountFrequency (%)
1184 1
1.0%
691 1
1.0%
435 1
1.0%
399 1
1.0%
376 1
1.0%
338 1
1.0%
320 1
1.0%
266 1
1.0%
265 1
1.0%
251 1
1.0%

유제품
Categorical

CONSTANT 

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

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
유제품 99
100.0%

Length

2023-12-10T15:36:30.887452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:36:31.026224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
유제품 99
100.0%

전체
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size924.0 B
전체
65 
연유
34 

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 65
65.7%
연유 34
34.3%

Length

2023-12-10T15:36:31.179135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:36:31.335698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
전체 65
65.7%
연유 34
34.3%

전체.1
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size924.0 B
전체
65 
연유
34 

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 65
65.7%
연유 34
34.3%

Length

2023-12-10T15:36:31.502999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:36:31.656821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
전체 65
65.7%
연유 34
34.3%

2
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size924.0 B
1
53 
2
46 

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 (%)
1 53
53.5%
2 46
46.5%

Length

2023-12-10T15:36:31.894157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:36:32.048187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 53
53.5%
2 46
46.5%

99
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)5.1%
Missing0
Missing (%)0.0%
Memory size924.0 B
20
38 
50
22 
30
15 
99
12 
40
12 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row99
2nd row99
3rd row99
4th row99
5th row99

Common Values

ValueCountFrequency (%)
20 38
38.4%
50 22
22.2%
30 15
 
15.2%
99 12
 
12.1%
40 12
 
12.1%

Length

2023-12-10T15:36:32.200776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:36:32.362497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
20 38
38.4%
50 22
22.2%
30 15
 
15.2%
99 12
 
12.1%
40 12
 
12.1%

인천광역시
Categorical

HIGH CORRELATION 

Distinct12
Distinct (%)12.1%
Missing0
Missing (%)0.0%
Memory size924.0 B
서울특별시
21 
경기도
19 
부산광역시
13 
전라북도
10 
경상남도
9 
Other values (7)
27 

Length

Max length5
Median length4
Mean length4.2525253
Min length3

Unique

Unique2 ?
Unique (%)2.0%

Sample

1st row경기도
2nd row경기도
3rd row경기도
4th row경기도
5th row충청북도

Common Values

ValueCountFrequency (%)
서울특별시 21
21.2%
경기도 19
19.2%
부산광역시 13
13.1%
전라북도 10
10.1%
경상남도 9
9.1%
충청북도 6
 
6.1%
전라남도 6
 
6.1%
대구광역시 5
 
5.1%
인천광역시 5
 
5.1%
경상북도 3
 
3.0%
Other values (2) 2
 
2.0%

Length

2023-12-10T15:36:32.575001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
서울특별시 21
21.2%
경기도 19
19.2%
부산광역시 13
13.1%
전라북도 10
10.1%
경상남도 9
9.1%
충청북도 6
 
6.1%
전라남도 6
 
6.1%
대구광역시 5
 
5.1%
인천광역시 5
 
5.1%
경상북도 3
 
3.0%
Other values (2) 2
 
2.0%

연수구
Categorical

HIGH CORRELATION 

Distinct33
Distinct (%)33.3%
Missing0
Missing (%)0.0%
Memory size924.0 B
전체
18 
중구
7 
청주시
 
4
성북구
 
3
양산시
 
3
Other values (28)
64 

Length

Max length4
Median length3
Mean length2.7979798
Min length2

Unique

Unique5 ?
Unique (%)5.1%

Sample

1st row전체
2nd row의정부시
3rd row안양시
4th row남양주시
5th row청주시

Common Values

ValueCountFrequency (%)
전체 18
 
18.2%
중구 7
 
7.1%
청주시 4
 
4.0%
성북구 3
 
3.0%
양산시 3
 
3.0%
남양주시 3
 
3.0%
남원시 3
 
3.0%
목포시 3
 
3.0%
김해시 3
 
3.0%
송파구 3
 
3.0%
Other values (23) 49
49.5%

Length

2023-12-10T15:36:32.924526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
전체 18
 
18.2%
중구 7
 
7.1%
청주시 4
 
4.0%
안양시 3
 
3.0%
마포구 3
 
3.0%
사상구 3
 
3.0%
동래구 3
 
3.0%
의정부시 3
 
3.0%
강서구 3
 
3.0%
노원구 3
 
3.0%
Other values (23) 49
49.5%

75
Real number (ℝ)

Distinct67
Distinct (%)67.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean97.090909
Minimum31
Maximum326
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1023.0 B
2023-12-10T15:36:33.156597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum31
5-th percentile35.9
Q178
median92
Q3108.5
95-th percentile168.9
Maximum326
Range295
Interquartile range (IQR)30.5

Descriptive statistics

Standard deviation40.456853
Coefficient of variation (CV)0.41669043
Kurtosis10.344758
Mean97.090909
Median Absolute Deviation (MAD)16
Skewness2.2431515
Sum9612
Variance1636.757
MonotonicityNot monotonic
2023-12-10T15:36:33.376680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
91 5
 
5.1%
92 3
 
3.0%
95 3
 
3.0%
83 3
 
3.0%
104 2
 
2.0%
115 2
 
2.0%
90 2
 
2.0%
98 2
 
2.0%
102 2
 
2.0%
108 2
 
2.0%
Other values (57) 73
73.7%
ValueCountFrequency (%)
31 2
2.0%
33 1
1.0%
34 1
1.0%
35 1
1.0%
36 1
1.0%
38 1
1.0%
49 1
1.0%
55 1
1.0%
59 1
1.0%
61 2
2.0%
ValueCountFrequency (%)
326 1
1.0%
221 1
1.0%
182 1
1.0%
180 1
1.0%
177 1
1.0%
168 1
1.0%
159 1
1.0%
158 1
1.0%
135 1
1.0%
133 1
1.0%

Interactions

2023-12-10T15:36:27.205628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:36:25.362724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:36:25.965529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:36:26.612753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:36:27.367369image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:36:25.526806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:36:26.109374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:36:26.752903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:36:27.549709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:36:25.661323image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:36:26.248697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:36:26.877422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:36:27.767949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:36:25.826929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:36:26.465029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:36:27.036999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T15:36:33.547487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
21879218.1전체전체.1299인천광역시연수구75
2181.0000.3041.0000.1510.1510.1540.1860.5670.6450.387
790.3041.0000.3040.6260.6260.4920.4370.4110.5520.635
218.11.0000.3041.0000.1510.1510.1540.1860.5670.6450.387
전체0.1510.6260.1511.0000.9990.9251.0000.0000.0000.000
전체.10.1510.6260.1510.9991.0000.9251.0000.0000.0000.000
20.1540.4920.1540.9250.9251.0001.0000.0820.0000.465
990.1860.4370.1861.0001.0001.0001.0000.4570.0000.385
인천광역시0.5670.4110.5670.0000.0000.0820.4571.0000.9650.555
연수구0.6450.5520.6450.0000.0000.0000.0000.9651.0000.690
750.3870.6350.3870.0000.0000.4650.3850.5550.6901.000
2023-12-10T15:36:33.781071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연수구인천광역시99전체.12전체
연수구1.0000.6670.0000.0000.0000.000
인천광역시0.6671.0000.2610.0000.0500.000
990.0000.2611.0000.9840.9840.984
전체.10.0000.0000.9841.0000.7520.977
20.0000.0500.9840.7521.0000.752
전체0.0000.0000.9840.9770.7521.000
2023-12-10T15:36:33.964254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
21879218.175전체전체.1299인천광역시연수구
2181.0000.4081.0000.2530.1040.1040.1060.1240.2460.284
790.4081.0000.4080.4020.6570.6570.5140.2940.2050.217
218.11.0000.4081.0000.2530.1040.1040.1060.1240.2460.284
750.2530.4020.2531.0000.0000.0000.3590.2450.2620.296
전체0.1040.6570.1040.0001.0000.9770.7520.9840.0000.000
전체.10.1040.6570.1040.0000.9771.0000.7520.9840.0000.000
20.1060.5140.1060.3590.7520.7521.0000.9840.0500.000
990.1240.2940.1240.2450.9840.9840.9841.0000.2610.000
인천광역시0.2460.2050.2460.2620.0000.0000.0500.2611.0000.667
연수구0.2840.2170.2840.2960.0000.0000.0000.0000.6671.000

Missing values

2023-12-10T15:36:28.351025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T15:36:28.666160image/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

MT20190121879218.1유제품전체전체.1299인천광역시연수구75
0MT201901164127164유제품전체전체299경기도전체83
1MT2019015415954유제품전체전체299경기도의정부시49
2MT201901428542유제품전체전체299경기도안양시77
3MT20190120777207유제품전체전체299경기도남양주시177
4MT20190169173691유제품전체전체299충청북도청주시61
5MT20190115251152유제품전체전체299전라북도전체55
6MT201901194319유제품전체전체299전라북도남원시92
7MT201901435107435유제품전체전체299전라남도전체129
8MT201901976797유제품전체전체299전라남도목포시35
9MT201901102161102유제품전체전체299경상남도김해시159
MT20190121879218.1유제품전체전체.1299인천광역시연수구75
89MT201901126221126유제품연유연유250인천광역시전체91
90MT201901102358102유제품연유연유250인천광역시연수구96
91MT201901141178141유제품연유연유250경기도전체88
92MT201901168148168유제품연유연유250경기도의정부시95
93MT201901118106118유제품연유연유250경기도안양시69
94MT201901657665유제품연유연유250경기도부천시74
95MT201901249883249유제품연유연유250경기도평택시76
96MT201901265206265유제품연유연유250경기도남양주시103
97MT201901106521106유제품연유연유250경기도오산시158
98MT201901139232139유제품연유연유250충청북도청주시77