Overview

Dataset statistics

Number of variables3
Number of observations100
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.8 KiB
Average record size in memory28.3 B

Variable types

Numeric3

Alerts

lsr_cd has unique valuesUnique

Reproduction

Analysis started2023-12-10 10:18:36.184350
Analysis finished2023-12-10 10:18:37.678133
Duration1.49 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

lsr_cd
Real number (ℝ)

UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean18210.86
Minimum19
Maximum79406
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:18:37.790566image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19
5-th percentile140.95
Q111623.75
median20327.5
Q323212
95-th percentile24464.65
Maximum79406
Range79387
Interquartile range (IQR)11588.25

Descriptive statistics

Standard deviation13710.197
Coefficient of variation (CV)0.75285831
Kurtosis10.234255
Mean18210.86
Median Absolute Deviation (MAD)3859.5
Skewness2.3604475
Sum1821086
Variance1.8796951 Γ— 108
MonotonicityNot monotonic
2023-12-10T19:18:38.016757image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
19 1
 
1.0%
20628 1
 
1.0%
23130 1
 
1.0%
23121 1
 
1.0%
23120 1
 
1.0%
23038 1
 
1.0%
23035 1
 
1.0%
22000 1
 
1.0%
21968 1
 
1.0%
21019 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
19 1
1.0%
31 1
1.0%
108 1
1.0%
124 1
1.0%
140 1
1.0%
141 1
1.0%
197 1
1.0%
268 1
1.0%
744 1
1.0%
796 1
1.0%
ValueCountFrequency (%)
79406 1
1.0%
79405 1
1.0%
79404 1
1.0%
24478 1
1.0%
24477 1
1.0%
24464 1
1.0%
24415 1
1.0%
24403 1
1.0%
24402 1
1.0%
24399 1
1.0%

lsr_la
Real number (ℝ)

Distinct93
Distinct (%)93.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean36.508541
Minimum33.433179
Maximum38.077598
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:18:38.185576image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum33.433179
5-th percentile33.433179
Q135.813969
median37.174099
Q337.552463
95-th percentile37.76796
Maximum38.077598
Range4.6444191
Interquartile range (IQR)1.7384938

Descriptive statistics

Standard deviation1.2897288
Coefficient of variation (CV)0.035326769
Kurtosis0.15146397
Mean36.508541
Median Absolute Deviation (MAD)0.60417556
Skewness-1.0019569
Sum3650.8541
Variance1.6634004
MonotonicityNot monotonic
2023-12-10T19:18:38.368961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
33.4331793245 6
 
6.0%
35.81513481291563 2
 
2.0%
37.526230419320015 2
 
2.0%
35.81347557614919 1
 
1.0%
36.4653158294 1
 
1.0%
37.1778523415 1
 
1.0%
35.1514596002 1
 
1.0%
35.82015489600404 1
 
1.0%
35.820172921188 1
 
1.0%
35.8151348129 1
 
1.0%
Other values (83) 83
83.0%
ValueCountFrequency (%)
33.4331793245 6
6.0%
33.43964477102691 1
 
1.0%
33.512995872 1
 
1.0%
34.6692433816 1
 
1.0%
34.68307872539128 1
 
1.0%
34.7529491566 1
 
1.0%
34.774373181312946 1
 
1.0%
35.0982429711 1
 
1.0%
35.1176061706 1
 
1.0%
35.1514596002 1
 
1.0%
ValueCountFrequency (%)
38.07759839166939 1
1.0%
38.07759275 1
1.0%
37.8060203704312 1
1.0%
37.78979285466571 1
1.0%
37.78973420737956 1
1.0%
37.76681395442574 1
1.0%
37.74347487700685 1
1.0%
37.664553197 1
1.0%
37.66455319697784 1
1.0%
37.65664535823991 1
1.0%

lsr_lo
Real number (ℝ)

Distinct93
Distinct (%)93.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.36374
Minimum126.50698
Maximum129.21164
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:18:38.595194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.50698
5-th percentile126.69489
Q1126.92584
median127.08201
Q3127.61337
95-th percentile128.95559
Maximum129.21164
Range2.7046529
Interquartile range (IQR)0.68752853

Descriptive statistics

Standard deviation0.72026615
Coefficient of variation (CV)0.0056551899
Kurtosis0.53482706
Mean127.36374
Median Absolute Deviation (MAD)0.19641005
Skewness1.3263045
Sum12736.374
Variance0.51878333
MonotonicityNot monotonic
2023-12-10T19:18:38.811059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126.9269629391 6
 
6.0%
127.15218589567792 2
 
2.0%
126.93105454082814 2
 
2.0%
127.1529085888861 1
 
1.0%
128.2771511918 1
 
1.0%
128.4701478498 1
 
1.0%
129.061108152 1
 
1.0%
127.1089877211988 1
 
1.0%
127.10898774583686 1
 
1.0%
127.1521858957 1
 
1.0%
Other values (83) 83
83.0%
ValueCountFrequency (%)
126.5069831003 1
1.0%
126.5366737911 1
1.0%
126.5766138845 1
1.0%
126.65368452882538 1
1.0%
126.667503276 1
1.0%
126.69633077813111 1
1.0%
126.70208472573704 1
1.0%
126.73307745027698 1
1.0%
126.7339228001 1
1.0%
126.75452647169588 1
1.0%
ValueCountFrequency (%)
129.2116360482 1
1.0%
129.2035301534543 1
1.0%
129.061108152 1
1.0%
129.045062436 1
1.0%
129.0289072971 1
1.0%
128.95173194851702 1
1.0%
128.948462 1
1.0%
128.9218370394 1
1.0%
128.86548767617592 1
1.0%
128.8044362131 1
1.0%

Interactions

2023-12-10T19:18:37.122519image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:18:36.283134image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:18:36.761093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:18:37.266659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:18:36.491458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:18:36.879878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:18:37.387616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:18:36.617931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:18:36.996109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T19:18:38.944682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
lsr_cdlsr_lalsr_lo
lsr_cd1.0000.3240.000
lsr_la0.3241.0000.865
lsr_lo0.0000.8651.000
2023-12-10T19:18:39.081131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
lsr_cdlsr_lalsr_lo
lsr_cd1.000-0.2550.005
lsr_la-0.2551.000-0.173
lsr_lo0.005-0.1731.000

Missing values

2023-12-10T19:18:37.528465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T19:18:37.636279image/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

lsr_cdlsr_lalsr_lo
01935.815135127.152186
17940437.170345128.948462
23135.74181127.137779
310837.244651127.615755
412437.574266126.984876
514037.433707126.786201
614136.962981128.39243
77940537.511311127.09814
819737.497757127.040978
926836.886062126.822634
lsr_cdlsr_lalsr_lo
902425537.499364126.853537
912438937.520205126.931802
922439235.749643127.122395
932439937.561441127.038396
942440237.553518126.921718
952440334.669243127.766968
962441537.57192126.987267
972446437.789793126.696331
982447736.002361127.66253
992447835.641115127.518109