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

Categorical10
Numeric2

Dataset

DescriptionSample
Author(주)제로투원파트너스
URLhttps://www.bigdata-telecom.kr/invoke/SOKBP2603/?goodsCode=ZTO010BSICGIHEALTHM

Alerts

MT has constant value ""Constant
201803 has constant value ""Constant
건강측정기기 has constant value ""Constant
전체 has constant value ""Constant
전체.1 has constant value ""Constant
2 has constant value ""Constant
대연엔터프라이즈 has constant value ""Constant
서울특별시 is highly overall correlated with 전체.2High correlation
전체.2 is highly overall correlated with 서울특별시High correlation

Reproduction

Analysis started2023-12-10 06:34:46.497519
Analysis finished2023-12-10 06:34:48.343202
Duration1.85 second
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

2023-12-10T15:34:48.505674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:34:48.682551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
mt 99
100.0%

201803
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size924.0 B
201803
99 

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 99
100.0%

Length

2023-12-10T15:34:49.264853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:34:49.426201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
201803 99
100.0%

121
Real number (ℝ)

Distinct76
Distinct (%)76.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean119.0101
Minimum25
Maximum335
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1023.0 B
2023-12-10T15:34:49.592000image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum25
5-th percentile44.8
Q169
median100
Q3151
95-th percentile249.3
Maximum335
Range310
Interquartile range (IQR)82

Descriptive statistics

Standard deviation63.684569
Coefficient of variation (CV)0.53511903
Kurtosis0.94033647
Mean119.0101
Median Absolute Deviation (MAD)36
Skewness1.080352
Sum11782
Variance4055.7244
MonotonicityNot monotonic
2023-12-10T15:34:49.811700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
100 4
 
4.0%
144 3
 
3.0%
67 3
 
3.0%
60 3
 
3.0%
130 3
 
3.0%
74 2
 
2.0%
75 2
 
2.0%
51 2
 
2.0%
92 2
 
2.0%
94 2
 
2.0%
Other values (66) 73
73.7%
ValueCountFrequency (%)
25 1
1.0%
27 1
1.0%
36 1
1.0%
42 1
1.0%
43 1
1.0%
45 1
1.0%
48 1
1.0%
51 2
2.0%
53 1
1.0%
54 1
1.0%
ValueCountFrequency (%)
335 1
1.0%
298 1
1.0%
277 1
1.0%
257 1
1.0%
252 1
1.0%
249 1
1.0%
223 1
1.0%
222 1
1.0%
219 1
1.0%
218 1
1.0%

44
Real number (ℝ)

Distinct38
Distinct (%)38.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean82.727273
Minimum13
Maximum100
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1023.0 B
2023-12-10T15:34:50.032979image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum13
5-th percentile39.6
Q168
median100
Q3100
95-th percentile100
Maximum100
Range87
Interquartile range (IQR)32

Descriptive statistics

Standard deviation21.847252
Coefficient of variation (CV)0.26408766
Kurtosis0.42096878
Mean82.727273
Median Absolute Deviation (MAD)0
Skewness-1.0932569
Sum8190
Variance477.30241
MonotonicityNot monotonic
2023-12-10T15:34:50.251203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=38)
ValueCountFrequency (%)
100 52
52.5%
65 3
 
3.0%
46 2
 
2.0%
69 2
 
2.0%
85 2
 
2.0%
73 2
 
2.0%
82 2
 
2.0%
59 2
 
2.0%
72 2
 
2.0%
57 2
 
2.0%
Other values (28) 28
28.3%
ValueCountFrequency (%)
13 1
1.0%
21 1
1.0%
33 1
1.0%
34 1
1.0%
36 1
1.0%
40 1
1.0%
44 1
1.0%
46 2
2.0%
47 1
1.0%
55 1
1.0%
ValueCountFrequency (%)
100 52
52.5%
89 1
 
1.0%
88 1
 
1.0%
85 2
 
2.0%
83 1
 
1.0%
82 2
 
2.0%
81 1
 
1.0%
80 1
 
1.0%
79 1
 
1.0%
77 1
 
1.0%

건강측정기기
Categorical

CONSTANT 

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

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
건강측정기기 99
100.0%

Length

2023-12-10T15:34:50.435893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:34:50.573847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
건강측정기기 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

2023-12-10T15:34:50.726647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:34:50.864087image/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

2023-12-10T15:34:51.039912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:34:51.211357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
전체 99
100.0%

2
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size924.0 B
2
99 

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 99
100.0%

Length

2023-12-10T15:34:51.388266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:34:51.536146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 99
100.0%

20
Categorical

Distinct3
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Memory size924.0 B
30
42 
20
39 
40
18 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row20
2nd row20
3rd row20
4th row20
5th row20

Common Values

ValueCountFrequency (%)
30 42
42.4%
20 39
39.4%
40 18
18.2%

Length

2023-12-10T15:34:51.683118image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:34:51.839329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
30 42
42.4%
20 39
39.4%
40 18
18.2%

서울특별시
Categorical

HIGH CORRELATION 

Distinct17
Distinct (%)17.2%
Missing0
Missing (%)0.0%
Memory size924.0 B
경기도
18 
충청남도
14 
서울특별시
8 
인천광역시
7 
부산광역시
7 
Other values (12)
45 

Length

Max length7
Median length5
Mean length4.2121212
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row서울특별시
2nd row부산광역시
3rd row인천광역시
4th row인천광역시
5th row대전광역시

Common Values

ValueCountFrequency (%)
경기도 18
18.2%
충청남도 14
14.1%
서울특별시 8
8.1%
인천광역시 7
 
7.1%
부산광역시 7
 
7.1%
울산광역시 6
 
6.1%
강원도 6
 
6.1%
경상남도 6
 
6.1%
전라북도 4
 
4.0%
제주특별자치도 4
 
4.0%
Other values (7) 19
19.2%

Length

2023-12-10T15:34:52.022846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
경기도 18
18.2%
충청남도 14
14.1%
서울특별시 8
8.1%
인천광역시 7
 
7.1%
부산광역시 7
 
7.1%
울산광역시 6
 
6.1%
강원도 6
 
6.1%
경상남도 6
 
6.1%
전라남도 4
 
4.0%
광주광역시 4
 
4.0%
Other values (7) 19
19.2%

전체.2
Categorical

HIGH CORRELATION 

Distinct40
Distinct (%)40.4%
Missing0
Missing (%)0.0%
Memory size924.0 B
전체
16 
북구
 
4
안산시
 
3
서구
 
3
서산시
 
3
Other values (35)
70 

Length

Max length4
Median length3
Mean length2.7676768
Min length2

Unique

Unique6 ?
Unique (%)6.1%

Sample

1st row구로구
2nd row금정구
3rd row부평구
4th row계양구
5th row유성구

Common Values

ValueCountFrequency (%)
전체 16
 
16.2%
북구 4
 
4.0%
안산시 3
 
3.0%
서구 3
 
3.0%
서산시 3
 
3.0%
안성시 3
 
3.0%
의왕시 3
 
3.0%
구로구 3
 
3.0%
유성구 3
 
3.0%
부평구 3
 
3.0%
Other values (30) 55
55.6%

Length

2023-12-10T15:34:52.314550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
전체 16
 
16.2%
북구 4
 
4.0%
안산시 3
 
3.0%
서구 3
 
3.0%
서산시 3
 
3.0%
안성시 3
 
3.0%
의왕시 3
 
3.0%
구로구 3
 
3.0%
유성구 3
 
3.0%
부평구 3
 
3.0%
Other values (30) 55
55.6%

대연엔터프라이즈
Categorical

CONSTANT 

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

Length

Max length9
Median length9
Mean length9
Min length9

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
대연엔터프라이즈 99
100.0%

Length

2023-12-10T15:34:52.552341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:34:52.752824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
대연엔터프라이즈 99
100.0%

Interactions

2023-12-10T15:34:47.370104image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:34:47.047373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:34:47.529802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:34:47.216291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T15:34:52.909816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
1214420서울특별시전체.2
1211.0000.0000.1620.6000.696
440.0001.0000.2350.4460.000
200.1620.2351.0000.0000.000
서울특별시0.6000.4460.0001.0000.980
전체.20.6960.0000.0000.9801.000
2023-12-10T15:34:53.069770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
20서울특별시전체.2
201.0000.0000.000
서울특별시0.0001.0000.670
전체.20.0000.6701.000
2023-12-10T15:34:53.215964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
1214420서울특별시전체.2
1211.000-0.1020.1140.2670.231
44-0.1021.0000.0980.1820.000
200.1140.0981.0000.0000.000
서울특별시0.2670.1820.0001.0000.670
전체.20.2310.0000.0000.6701.000

Missing values

2023-12-10T15:34:47.768520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T15:34:48.216870image/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

MT20180312144건강측정기기전체전체.1220서울특별시전체.2대연엔터프라이즈
0MT201803144100건강측정기기전체전체220서울특별시구로구대연엔터프라이즈
1MT20180358100건강측정기기전체전체220부산광역시금정구대연엔터프라이즈
2MT20180315170건강측정기기전체전체220인천광역시부평구대연엔터프라이즈
3MT20180357100건강측정기기전체전체220인천광역시계양구대연엔터프라이즈
4MT20180320567건강측정기기전체전체220대전광역시유성구대연엔터프라이즈
5MT201803136100건강측정기기전체전체220울산광역시남구대연엔터프라이즈
6MT20180399100건강측정기기전체전체220경기도동두천시대연엔터프라이즈
7MT2018039365건강측정기기전체전체220경기도안산시대연엔터프라이즈
8MT20180367100건강측정기기전체전체220경기도의왕시대연엔터프라이즈
9MT20180360100건강측정기기전체전체220경기도안성시대연엔터프라이즈
MT20180312144건강측정기기전체전체.1220서울특별시전체.2대연엔터프라이즈
89MT201803335100건강측정기기전체전체230경기도양평군대연엔터프라이즈
90MT20180315875건강측정기기전체전체230강원도춘천시대연엔터프라이즈
91MT20180322261건강측정기기전체전체230강원도원주시대연엔터프라이즈
92MT20180312346건강측정기기전체전체230충청남도천안시대연엔터프라이즈
93MT2018039760건강측정기기전체전체230전라북도전주시대연엔터프라이즈
94MT20180317572건강측정기기전체전체230전라북도군산시대연엔터프라이즈
95MT20180312683건강측정기기전체전체230경상남도전체대연엔터프라이즈
96MT20180315189건강측정기기전체전체230경상남도창원시대연엔터프라이즈
97MT20180311369건강측정기기전체전체230제주특별자치도전체대연엔터프라이즈
98MT20180311369건강측정기기전체전체230제주특별자치도제주시대연엔터프라이즈