Overview

Dataset statistics

Number of variables5
Number of observations500
Missing cells5
Missing cells (%)0.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory22.1 KiB
Average record size in memory45.3 B

Variable types

Numeric3
Categorical2

Alerts

HHS_CONTE_VAL has constant value ""Constant
YM has constant value ""Constant

Reproduction

Analysis started2024-03-13 12:47:10.484997
Analysis finished2024-03-13 12:47:12.180622
Duration1.7 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

LA
Real number (ℝ)

Distinct6
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-74.454
Minimum-89.5
Maximum-72.5
Zeros0
Zeros (%)0.0%
Negative500
Negative (%)100.0%
Memory size4.5 KiB
2024-03-13T21:47:12.740663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-89.5
5-th percentile-76.5
Q1-75.5
median-74.5
Q3-73.5
95-th percentile-72.5
Maximum-72.5
Range17
Interquartile range (IQR)2

Descriptive statistics

Standard deviation2.0199119
Coefficient of variation (CV)-0.027129663
Kurtosis28.564053
Mean-74.454
Median Absolute Deviation (MAD)1
Skewness-4.1264934
Sum-37227
Variance4.0800441
MonotonicityIncreasing
2024-03-13T21:47:12.895804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
-73.5 131
26.2%
-74.5 105
21.0%
-72.5 100
20.0%
-75.5 85
17.0%
-76.5 74
14.8%
-89.5 5
 
1.0%
ValueCountFrequency (%)
-89.5 5
 
1.0%
-76.5 74
14.8%
-75.5 85
17.0%
-74.5 105
21.0%
-73.5 131
26.2%
-72.5 100
20.0%
ValueCountFrequency (%)
-72.5 100
20.0%
-73.5 131
26.2%
-74.5 105
21.0%
-75.5 85
17.0%
-76.5 74
14.8%
-89.5 5
 
1.0%

LO
Real number (ℝ)

Distinct158
Distinct (%)31.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-75.694
Minimum-179
Maximum180
Zeros0
Zeros (%)0.0%
Negative439
Negative (%)87.8%
Memory size4.5 KiB
2024-03-13T21:47:13.076653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-179
5-th percentile-175
Q1-155.25
median-111
Q3-39.75
95-th percentile174
Maximum180
Range359
Interquartile range (IQR)115.5

Descriptive statistics

Standard deviation105.4079
Coefficient of variation (CV)-1.392553
Kurtosis1.0061053
Mean-75.694
Median Absolute Deviation (MAD)56
Skewness1.3920655
Sum-37847
Variance11110.826
MonotonicityNot monotonic
2024-03-13T21:47:13.245137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-179 6
 
1.2%
-177 6
 
1.2%
-176 6
 
1.2%
-175 6
 
1.2%
-178 6
 
1.2%
-156 5
 
1.0%
-160 5
 
1.0%
-159 5
 
1.0%
-158 5
 
1.0%
-157 5
 
1.0%
Other values (148) 445
89.0%
ValueCountFrequency (%)
-179 6
1.2%
-178 6
1.2%
-177 6
1.2%
-176 6
1.2%
-175 6
1.2%
-174 5
1.0%
-173 5
1.0%
-172 5
1.0%
-171 5
1.0%
-170 5
1.0%
ValueCountFrequency (%)
180 4
0.8%
179 4
0.8%
178 4
0.8%
177 4
0.8%
176 4
0.8%
175 4
0.8%
174 4
0.8%
173 4
0.8%
172 4
0.8%
171 4
0.8%

HHS_CONTE_VAL
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
0
500 

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 (%)
0 500
100.0%

Length

2024-03-13T21:47:13.401244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T21:47:13.561379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 500
100.0%

SOHTC300_VAL
Real number (ℝ)

Distinct413
Distinct (%)83.4%
Missing5
Missing (%)1.0%
Infinite0
Infinite (%)0.0%
Mean-72563301
Minimum-1.67 × 109
Maximum1.11 × 109
Zeros0
Zeros (%)0.0%
Negative199
Negative (%)39.8%
Memory size4.5 KiB
2024-03-13T21:47:13.707836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-1.67 × 109
5-th percentile-1.013 × 109
Q1-1.245 × 108
median47300000
Q31.33 × 108
95-th percentile2.897 × 108
Maximum1.11 × 109
Range2.78 × 109
Interquartile range (IQR)2.575 × 108

Descriptive statistics

Standard deviation4.2225159 × 108
Coefficient of variation (CV)-5.8190791
Kurtosis3.0949306
Mean-72563301
Median Absolute Deviation (MAD)1.087 × 108
Skewness-1.3983065
Sum-3.5918834 × 1010
Variance1.782964 × 1017
MonotonicityNot monotonic
2024-03-13T21:47:13.918239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
128000000.0 6
 
1.2%
118000000.0 4
 
0.8%
156000000.0 4
 
0.8%
139000000.0 3
 
0.6%
149000000.0 3
 
0.6%
161000000.0 3
 
0.6%
176000000.0 3
 
0.6%
175000000.0 3
 
0.6%
181000000.0 3
 
0.6%
160000000.0 3
 
0.6%
Other values (403) 460
92.0%
(Missing) 5
 
1.0%
ValueCountFrequency (%)
-1670000000.0 1
0.2%
-1660000000.0 1
0.2%
-1650000000.0 1
0.2%
-1550000000.0 1
0.2%
-1530000000.0 1
0.2%
-1490000000.0 1
0.2%
-1450000000.0 1
0.2%
-1370000000.0 1
0.2%
-1360000000.0 1
0.2%
-1310000000.0 1
0.2%
ValueCountFrequency (%)
1110000000.0 1
0.2%
1070000000.0 1
0.2%
1060000000.0 2
0.4%
1050000000.0 1
0.2%
1040000000.0 1
0.2%
935000000.0 1
0.2%
792000000.0 1
0.2%
727000000.0 1
0.2%
711000000.0 1
0.2%
676000000.0 1
0.2%

YM
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
197901
500 

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row197901
2nd row197901
3rd row197901
4th row197901
5th row197901

Common Values

ValueCountFrequency (%)
197901 500
100.0%

Length

2024-03-13T21:47:14.061042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T21:47:14.206859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
197901 500
100.0%

Interactions

2024-03-13T21:47:11.518698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:47:10.640790image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:47:11.089944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:47:11.652847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:47:10.786015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:47:11.242713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:47:11.793310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:47:10.941954image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:47:11.391545image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-13T21:47:14.282247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
LALOSOHTC300_VAL
LA1.0000.3950.474
LO0.3951.0000.691
SOHTC300_VAL0.4740.6911.000
2024-03-13T21:47:14.417066image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
LALOSOHTC300_VAL
LA1.000-0.142-0.377
LO-0.1421.0000.028
SOHTC300_VAL-0.3770.0281.000

Missing values

2024-03-13T21:47:11.949276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-13T21:47:12.120691image/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

LALOHHS_CONTE_VALSOHTC300_VALYM
0-89.5-1790<NA>197901
1-89.5-1780<NA>197901
2-89.5-1770<NA>197901
3-89.5-1760<NA>197901
4-89.5-1750<NA>197901
5-76.5-1790-74600000.0197901
6-76.5-1780-197000000.0197901
7-76.5-1770-90000000.0197901
8-76.5-1760581504.0197901
9-76.5-175029900000.0197901
LALOHHS_CONTE_VALSOHTC300_VALYM
490-72.5-810-1670000000.0197901
491-72.5-800-1450000000.0197901
492-72.5-770-1490000000.0197901
493-72.5-760-1550000000.0197901
494-72.5-750-1650000000.0197901
495-72.5-740-1660000000.0197901
496-72.5-60012200000.0197901
497-72.5-59099900000.0197901
498-72.5-58052000000.0197901
499-72.5-57054100000.0197901