Overview

Dataset statistics

Number of variables7
Number of observations199
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory12.2 KiB
Average record size in memory62.7 B

Variable types

Categorical4
Numeric3

Dataset

DescriptionSample
Author한국스마트그리드
URLhttps://www.bigdata-telecom.kr/invoke/SOKBP2603/?goodsCode=KSGTEEMIMPUTE

Alerts

E000000001 has constant value ""Constant
2344 has constant value ""Constant
4125010700 has constant value ""Constant
0.0 has constant value ""Constant
00 has 8 (4.0%) zerosZeros

Reproduction

Analysis started2023-12-10 06:55:21.077765
Analysis finished2023-12-10 06:55:22.146214
Duration1.07 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

E000000001
Categorical

CONSTANT 

Distinct1
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
E000000001
199 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowE000000001
2nd rowE000000001
3rd rowE000000001
4th rowE000000001
5th rowE000000001

Common Values

ValueCountFrequency (%)
E000000001 199
100.0%

Length

2023-12-10T15:55:22.204712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:55:22.286371image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
e000000001 199
100.0%

2344
Categorical

CONSTANT 

Distinct1
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
2344
199 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2344
2nd row2344
3rd row2344
4th row2344
5th row2344

Common Values

ValueCountFrequency (%)
2344 199
100.0%

Length

2023-12-10T15:55:22.394198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:55:22.484205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2344 199
100.0%

4125010700
Categorical

CONSTANT 

Distinct1
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
4125010700
199 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row4125010700
2nd row4125010700
3rd row4125010700
4th row4125010700
5th row4125010700

Common Values

ValueCountFrequency (%)
4125010700 199
100.0%

Length

2023-12-10T15:55:22.577697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:55:22.660182image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
4125010700 199
100.0%

20210701
Real number (ℝ)

Distinct9
Distinct (%)4.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20210705
Minimum20210701
Maximum20210709
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2023-12-10T15:55:22.735001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20210701
5-th percentile20210701
Q120210703
median20210705
Q320210707
95-th percentile20210708
Maximum20210709
Range8
Interquartile range (IQR)4

Descriptive statistics

Standard deviation2.4099012
Coefficient of variation (CV)1.1923885 × 10-7
Kurtosis-1.1761804
Mean20210705
Median Absolute Deviation (MAD)2
Skewness0.03119347
Sum4.0219302 × 109
Variance5.807624
MonotonicityIncreasing
2023-12-10T15:55:22.873091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
20210702 24
12.1%
20210703 24
12.1%
20210704 24
12.1%
20210705 24
12.1%
20210706 24
12.1%
20210707 24
12.1%
20210708 24
12.1%
20210701 23
11.6%
20210709 8
 
4.0%
ValueCountFrequency (%)
20210701 23
11.6%
20210702 24
12.1%
20210703 24
12.1%
20210704 24
12.1%
20210705 24
12.1%
20210706 24
12.1%
20210707 24
12.1%
20210708 24
12.1%
20210709 8
 
4.0%
ValueCountFrequency (%)
20210709 8
 
4.0%
20210708 24
12.1%
20210707 24
12.1%
20210706 24
12.1%
20210705 24
12.1%
20210704 24
12.1%
20210703 24
12.1%
20210702 24
12.1%
20210701 23
11.6%

00
Real number (ℝ)

ZEROS 

Distinct24
Distinct (%)12.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11.236181
Minimum0
Maximum23
Zeros8
Zeros (%)4.0%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2023-12-10T15:55:22.991457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q15
median11
Q317
95-th percentile22
Maximum23
Range23
Interquartile range (IQR)12

Descriptive statistics

Standard deviation6.9659705
Coefficient of variation (CV)0.61995891
Kurtosis-1.2249035
Mean11.236181
Median Absolute Deviation (MAD)6
Skewness0.060746037
Sum2236
Variance48.524745
MonotonicityNot monotonic
2023-12-10T15:55:23.095160image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
1 9
 
4.5%
3 9
 
4.5%
4 9
 
4.5%
5 9
 
4.5%
6 9
 
4.5%
7 9
 
4.5%
2 9
 
4.5%
17 8
 
4.0%
0 8
 
4.0%
23 8
 
4.0%
Other values (14) 112
56.3%
ValueCountFrequency (%)
0 8
4.0%
1 9
4.5%
2 9
4.5%
3 9
4.5%
4 9
4.5%
5 9
4.5%
6 9
4.5%
7 9
4.5%
8 8
4.0%
9 8
4.0%
ValueCountFrequency (%)
23 8
4.0%
22 8
4.0%
21 8
4.0%
20 8
4.0%
19 8
4.0%
18 8
4.0%
17 8
4.0%
16 8
4.0%
15 8
4.0%
14 8
4.0%

94.0769
Real number (ℝ)

Distinct138
Distinct (%)69.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.3231
Minimum5
Maximum275
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2023-12-10T15:55:23.218438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5
5-th percentile61.6
Q1105
median119
Q3145.0971
95-th percentile212
Maximum275
Range270
Interquartile range (IQR)40.0971

Descriptive statistics

Standard deviation44.941741
Coefficient of variation (CV)0.35297398
Kurtosis0.83796498
Mean127.3231
Median Absolute Deviation (MAD)21
Skewness0.53806498
Sum25337.296
Variance2019.76
MonotonicityNot monotonic
2023-12-10T15:55:23.361498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
108.0 8
 
4.0%
111.0 5
 
2.5%
117.0 5
 
2.5%
91.0 4
 
2.0%
109.0 4
 
2.0%
126.0 4
 
2.0%
114.0 4
 
2.0%
112.0 4
 
2.0%
123.0 4
 
2.0%
116.0 3
 
1.5%
Other values (128) 154
77.4%
ValueCountFrequency (%)
5.0 1
0.5%
10.0 1
0.5%
35.0 1
0.5%
38.83 1
0.5%
41.0 1
0.5%
42.1295 1
0.5%
46.0 1
0.5%
51.0 1
0.5%
57.0 1
0.5%
58.0 1
0.5%
ValueCountFrequency (%)
275.0 1
 
0.5%
266.0 1
 
0.5%
249.0 1
 
0.5%
236.0 1
 
0.5%
219.0 1
 
0.5%
217.0 1
 
0.5%
216.0 1
 
0.5%
215.0 1
 
0.5%
214.0 1
 
0.5%
212.0 3
1.5%

0.0
Categorical

CONSTANT 

Distinct1
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
0
199 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 199
100.0%

Length

2023-12-10T15:55:23.495881image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:55:23.598328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 199
100.0%

Interactions

2023-12-10T15:55:21.716917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:55:21.186159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:55:21.481814image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:55:21.829904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:55:21.286142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:55:21.562130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:55:21.910208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:55:21.391676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:55:21.630739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T15:55:23.660876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
202107010094.0769
202107011.0000.0000.451
000.0001.0000.707
94.07690.4510.7071.000
2023-12-10T15:55:23.750740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
202107010094.0769
202107011.000-0.0910.199
00-0.0911.0000.057
94.07690.1990.0571.000

Missing values

2023-12-10T15:55:22.003693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T15:55:22.105664image/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

E00000000123444125010700202107010094.07690.0
0E00000000123444125010700202107011108.56850
1E0000000012344412501070020210701298.92150
2E00000000123444125010700202107013144.3560
3E00000000123444125010700202107014150.85730
4E00000000123444125010700202107015136.32180
5E00000000123444125010700202107016204.00
6E00000000123444125010700202107017166.61570
7E00000000123444125010700202107018161.77630
8E00000000123444125010700202107019126.00
9E000000001234441250107002021070110120.00
E00000000123444125010700202107010094.07690.0
189E000000001234441250107002021070822127.00
190E000000001234441250107002021070823125.00
191E0000000012344412501070020210709091.00
192E0000000012344412501070020210709163.00
193E0000000012344412501070020210709294.05910
194E00000000123444125010700202107093143.33370
195E00000000123444125010700202107094157.14980
196E00000000123444125010700202107095146.01590
197E00000000123444125010700202107096266.00
198E00000000123444125010700202107097137.00