Overview

Dataset statistics

Number of variables5
Number of observations199
Missing cells0
Missing cells (%)0.0%
Duplicate rows1
Duplicate rows (%)0.5%
Total size in memory8.7 KiB
Average record size in memory44.7 B

Variable types

Categorical3
Numeric2

Alerts

DATE has constant value ""Constant
DAYWEEK has constant value ""Constant
Dataset has 1 (0.5%) duplicate rowsDuplicates
TELNO_RP_VALUE is highly overall correlated with TELOFCNOHigh correlation
TELOFCNO is highly overall correlated with TELNO_RP_VALUEHigh correlation

Reproduction

Analysis started2023-12-10 06:16:01.820456
Analysis finished2023-12-10 06:16:02.825312
Duration1 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

DATE
Categorical

CONSTANT 

Distinct1
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
20200101
199 

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row20200101
2nd row20200101
3rd row20200101
4th row20200101
5th row20200101

Common Values

ValueCountFrequency (%)
20200101 199
100.0%

Length

2023-12-10T15:16:02.916616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:16:03.070574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
20200101 199
100.0%

HMS
Real number (ℝ)

Distinct153
Distinct (%)76.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1732.603
Minimum208
Maximum3116
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2023-12-10T15:16:03.233812image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum208
5-th percentile340.8
Q11220.5
median1635
Q32281.5
95-th percentile2838.1
Maximum3116
Range2908
Interquartile range (IQR)1061

Descriptive statistics

Standard deviation760.44217
Coefficient of variation (CV)0.43890156
Kurtosis-0.78080175
Mean1732.603
Median Absolute Deviation (MAD)478
Skewness0.0083824823
Sum344788
Variance578272.29
MonotonicityIncreasing
2023-12-10T15:16:03.439844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2821 4
 
2.0%
2809 3
 
1.5%
2804 3
 
1.5%
1503 3
 
1.5%
330 3
 
1.5%
1728 3
 
1.5%
1131 3
 
1.5%
1943 2
 
1.0%
2048 2
 
1.0%
1436 2
 
1.0%
Other values (143) 171
85.9%
ValueCountFrequency (%)
208 1
 
0.5%
209 1
 
0.5%
254 1
 
0.5%
301 2
1.0%
318 2
1.0%
330 3
1.5%
342 1
 
0.5%
347 1
 
0.5%
448 1
 
0.5%
502 1
 
0.5%
ValueCountFrequency (%)
3116 1
0.5%
3114 2
1.0%
3058 1
0.5%
3055 1
0.5%
3051 1
0.5%
3022 1
0.5%
3020 1
0.5%
2842 1
0.5%
2839 1
0.5%
2838 1
0.5%

DAYWEEK
Categorical

CONSTANT 

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

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
WED 199
100.0%

Length

2023-12-10T15:16:03.656528image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:16:03.792164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
wed 199
100.0%

TELOFCNO
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
63
84 
51
35 
55
32 
53
30 
54
18 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row55
2nd row63
3rd row55
4th row51
5th row63

Common Values

ValueCountFrequency (%)
63 84
42.2%
51 35
17.6%
55 32
 
16.1%
53 30
 
15.1%
54 18
 
9.0%

Length

2023-12-10T15:16:03.945494image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:16:04.093599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
63 84
42.2%
51 35
17.6%
55 32
 
16.1%
53 30
 
15.1%
54 18
 
9.0%

TELNO_RP_VALUE
Real number (ℝ)

HIGH CORRELATION 

Distinct16
Distinct (%)8.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4616.7839
Minimum22
Maximum8888
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2023-12-10T15:16:04.276079image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum22
5-th percentile1856.2
Q12415
median3333
Q37777
95-th percentile8080
Maximum8888
Range8866
Interquartile range (IQR)5362

Descriptive statistics

Standard deviation2683.5065
Coefficient of variation (CV)0.58125018
Kurtosis-1.6003158
Mean4616.7839
Median Absolute Deviation (MAD)2222
Skewness0.21405817
Sum918740
Variance7201206.9
MonotonicityNot monotonic
2023-12-10T15:16:04.447329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
8080 36
18.1%
2415 32
16.1%
2082 22
11.1%
2459 22
11.1%
5808 17
8.5%
7106 12
 
6.0%
1939 12
 
6.0%
6003 11
 
5.5%
7777 10
 
5.0%
8888 7
 
3.5%
Other values (6) 18
9.0%
ValueCountFrequency (%)
22 3
 
1.5%
276 1
 
0.5%
1111 6
 
3.0%
1939 12
 
6.0%
2082 22
11.1%
2415 32
16.1%
2459 22
11.1%
3333 2
 
1.0%
3779 1
 
0.5%
3986 5
 
2.5%
ValueCountFrequency (%)
8888 7
 
3.5%
8080 36
18.1%
7777 10
 
5.0%
7106 12
 
6.0%
6003 11
 
5.5%
5808 17
8.5%
3986 5
 
2.5%
3779 1
 
0.5%
3333 2
 
1.0%
2459 22
11.1%

Interactions

2023-12-10T15:16:02.255566image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:16:01.978394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:16:02.402216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:16:02.127242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T15:16:04.594201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
HMSTELOFCNOTELNO_RP_VALUE
HMS1.0000.3130.302
TELOFCNO0.3131.0000.854
TELNO_RP_VALUE0.3020.8541.000
2023-12-10T15:16:04.724616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
HMSTELNO_RP_VALUETELOFCNO
HMS1.0000.0850.127
TELNO_RP_VALUE0.0851.0000.702
TELOFCNO0.1270.7021.000

Missing values

2023-12-10T15:16:02.581895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T15:16:02.766261image/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

DATEHMSDAYWEEKTELOFCNOTELNO_RP_VALUE
020200101208WED552415
120200101209WED638080
220200101254WED552415
320200101301WED511939
420200101301WED632082
520200101318WED512459
620200101318WED535808
720200101330WED548888
820200101330WED547777
920200101330WED631111
DATEHMSDAYWEEKTELOFCNOTELNO_RP_VALUE
189202001012839WED637106
190202001012842WED638080
191202001013020WED637106
192202001013022WED638080
193202001013051WED637106
194202001013055WED638080
195202001013058WED633986
196202001013114WED512459
197202001013114WED535808
198202001013116WED637106

Duplicate rows

Most frequently occurring

DATEHMSDAYWEEKTELOFCNOTELNO_RP_VALUE# duplicates
0202001011930WED5360032