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 06:25:53.921859
Analysis finished2023-12-10 06:25:55.038291
Duration1.12 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

2023-12-10T15:25:55.180200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:25:55.352467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
20200101 199
100.0%

HMS
Real number (ℝ)

Distinct197
Distinct (%)99.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean16989.99
Minimum209
Maximum62835
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2023-12-10T15:25:55.578027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum209
5-th percentile1037
Q13528
median12233
Q323186
95-th percentile53652.4
Maximum62835
Range62626
Interquartile range (IQR)19658

Descriptive statistics

Standard deviation15826.085
Coefficient of variation (CV)0.93149469
Kurtosis0.54738284
Mean16989.99
Median Absolute Deviation (MAD)9422
Skewness1.1729879
Sum3381008
Variance2.5046498 × 108
MonotonicityIncreasing
2023-12-10T15:25:55.839829image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1930 2
 
1.0%
2804 2
 
1.0%
209 1
 
0.5%
15646 1
 
0.5%
20019 1
 
0.5%
20043 1
 
0.5%
20653 1
 
0.5%
20709 1
 
0.5%
20759 1
 
0.5%
20948 1
 
0.5%
Other values (187) 187
94.0%
ValueCountFrequency (%)
209 1
0.5%
257 1
0.5%
342 1
0.5%
447 1
0.5%
503 1
0.5%
659 1
0.5%
753 1
0.5%
820 1
0.5%
941 1
0.5%
1019 1
0.5%
ValueCountFrequency (%)
62835 1
0.5%
62713 1
0.5%
55812 1
0.5%
55711 1
0.5%
55620 1
0.5%
55145 1
0.5%
55014 1
0.5%
54552 1
0.5%
54428 1
0.5%
53719 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

2023-12-10T15:25:56.153791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:25:56.327014image/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
42
103 
33
53 
41
39 
43
 
2
44
 
2

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row42
2nd row42
3rd row33
4th row42
5th row33

Common Values

ValueCountFrequency (%)
42 103
51.8%
33 53
26.6%
41 39
 
19.6%
43 2
 
1.0%
44 2
 
1.0%

Length

2023-12-10T15:25:56.477253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:25:56.705909image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
42 103
51.8%
33 53
26.6%
41 39
 
19.6%
43 2
 
1.0%
44 2
 
1.0%

TELNO_RP_VALUE
Real number (ℝ)

HIGH CORRELATION 

Distinct18
Distinct (%)9.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5277.5678
Minimum60
Maximum9478
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2023-12-10T15:25:56.909205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum60
5-th percentile271
Q11125
median8987
Q38987
95-th percentile8987
Maximum9478
Range9418
Interquartile range (IQR)7862

Descriptive statistics

Standard deviation4003.2617
Coefficient of variation (CV)0.75854291
Kurtosis-1.9076225
Mean5277.5678
Median Absolute Deviation (MAD)0
Skewness-0.20797584
Sum1050236
Variance16026104
MonotonicityNot monotonic
2023-12-10T15:25:57.104142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
8987 102
51.3%
1125 49
24.6%
271 33
 
16.6%
5431 1
 
0.5%
2785 1
 
0.5%
5050 1
 
0.5%
7978 1
 
0.5%
5252 1
 
0.5%
5607 1
 
0.5%
5464 1
 
0.5%
Other values (8) 8
 
4.0%
ValueCountFrequency (%)
60 1
 
0.5%
271 33
16.6%
1125 49
24.6%
1316 1
 
0.5%
2222 1
 
0.5%
2730 1
 
0.5%
2785 1
 
0.5%
3333 1
 
0.5%
5050 1
 
0.5%
5252 1
 
0.5%
ValueCountFrequency (%)
9478 1
 
0.5%
8987 102
51.3%
7978 1
 
0.5%
7155 1
 
0.5%
5633 1
 
0.5%
5607 1
 
0.5%
5464 1
 
0.5%
5431 1
 
0.5%
5252 1
 
0.5%
5050 1
 
0.5%

Interactions

2023-12-10T15:25:54.437045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:25:54.130683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:25:54.599367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:25:54.291387image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T15:25:57.226149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
HMSTELOFCNOTELNO_RP_VALUE
HMS1.0000.4720.321
TELOFCNO0.4721.0000.926
TELNO_RP_VALUE0.3210.9261.000
2023-12-10T15:25:57.369350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
HMSTELNO_RP_VALUETELOFCNO
HMS1.000-0.0140.212
TELNO_RP_VALUE-0.0141.0000.872
TELOFCNO0.2120.8721.000

Missing values

2023-12-10T15:25:54.790205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T15:25:54.965996image/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
020200101209WED428987
120200101257WED428987
220200101342WED331125
320200101447WED428987
420200101503WED331125
520200101659WED428987
620200101753WED428987
720200101820WED428987
820200101941WED413333
9202001011019WED428987
DATEHMSDAYWEEKTELOFCNOTELNO_RP_VALUE
1892020010153719WED331125
1902020010154428WED428987
1912020010154552WED428987
1922020010155014WED432785
1932020010155145WED331125
1942020010155620WED428987
1952020010155711WED331125
1962020010155812WED331125
1972020010162713WED428987
1982020010162835WED428987

Duplicate rows

Most frequently occurring

DATEHMSDAYWEEKTELOFCNOTELNO_RP_VALUE# duplicates
0202001011930WED3311252