Dataset statistics
Number of variables | 3 |
---|---|
Number of observations | 208 |
Missing cells | 146 |
Missing cells (%) | 23.4% |
Duplicate rows | 0 |
Duplicate rows (%) | 0.0% |
Total size in memory | 5.0 KiB |
Average record size in memory | 24.6 B |
Variable types
NUM | 2 |
---|---|
DATE | 1 |
Reproduction
Analysis started | 2020-08-18 00:53:39.329315 |
---|---|
Analysis finished | 2020-08-18 00:53:42.956855 |
Duration | 3.63 seconds |
Version | pandas-profiling v2.8.0 |
Command line | pandas_profiling --config_file config.yaml [YOUR_FILE.csv] |
Download configuration | config.yaml |
Recoveries is highly correlated with Predicted Recoveries | High correlation |
Predicted Recoveries is highly correlated with Recoveries | High correlation |
Recoveries has 146 (70.2%) missing values | Missing |
df_index has unique values | Unique |
Predicted Recoveries has unique values | Unique |
Distinct count | 208 |
---|---|
Unique (%) | 100.0% |
Missing | 0 |
Missing (%) | 0.0% |
Memory size | 1.8 KiB |
Minimum | 2020-01-22 00:00:00 |
---|---|
Maximum | 2020-08-16 00:00:00 |
Histogram
Distinct count | 208 |
---|---|
Unique (%) | 100.0% |
Missing | 0 |
Missing (%) | 0.0% |
Infinite | 0 |
Infinite (%) | 0.0% |
Mean | 67044.86530012194 |
---|---|
Minimum | 28.0 |
Maximum | 86889.08734432753 |
Zeros | 0 |
Zeros (%) | 0.0% |
Memory size | 1.8 KiB |
Quantile statistics
Minimum | 28 |
---|---|
5-th percentile | 215.1488657 |
Q1 | 65623.22521 |
median | 82818.89174 |
Q3 | 84171.81443 |
95-th percentile | 85595.70052 |
Maximum | 86889.08734 |
Range | 86861.08734 |
Interquartile range (IQR) | 18548.58921 |
Descriptive statistics
Standard deviation | 28839.30875 |
---|---|
Coefficient of variation (CV) | 0.4301494025 |
Kurtosis | 0.7213659654 |
Mean | 67044.8653 |
Median Absolute Deviation (MAD) | 2238.00389 |
Skewness | -1.531728373 |
Sum | 13945331.98 |
Variance | 831705729.3 |
Histogram with fixed size bins (bins=10)
Value | Count | Frequency (%) | |
84444.72682 | 1 | 0.5% | |
83340.54212 | 1 | 0.5% | |
83752.91135 | 1 | 0.5% | |
84988.96822 | 1 | 0.5% | |
51297.70501 | 1 | 0.5% | |
23287.2702 | 1 | 0.5% | |
80846.36946 | 1 | 0.5% | |
74156.62074 | 1 | 0.5% | |
80693.07469 | 1 | 0.5% | |
84000.21038 | 1 | 0.5% | |
75516.55169 | 1 | 0.5% | |
84878.42231 | 1 | 0.5% | |
83425.45168 | 1 | 0.5% | |
82603.52691 | 1 | 0.5% | |
79411.77536 | 1 | 0.5% | |
84661.10845 | 1 | 0.5% | |
83794.80432 | 1 | 0.5% | |
80533.8115 | 1 | 0.5% | |
84468.19594 | 1 | 0.5% | |
81134.46405 | 1 | 0.5% | |
76294.99055 | 1 | 0.5% | |
86506.48809 | 1 | 0.5% | |
82694.21002 | 1 | 0.5% | |
85349.42623 | 1 | 0.5% | |
83567.39632 | 1 | 0.5% | |
Other values (183) | 183 | 88.0% |
Value | Count | Frequency (%) | |
28 | 1 | 0.5% | |
30 | 1 | 0.5% | |
36 | 1 | 0.5% | |
39 | 1 | 0.5% | |
49 | 1 | 0.5% | |
58 | 1 | 0.5% | |
101 | 1 | 0.5% | |
120 | 1 | 0.5% | |
135 | 1 | 0.5% | |
163.91 | 1 | 0.5% |
Value | Count | Frequency (%) | |
86889.08734 | 1 | 0.5% | |
86761.81435 | 1 | 0.5% | |
86633.99392 | 1 | 0.5% | |
86506.48809 | 1 | 0.5% | |
86378.56784 | 1 | 0.5% | |
86249.07294 | 1 | 0.5% | |
86118.41177 | 1 | 0.5% | |
85989.80835 | 1 | 0.5% | |
85864.47135 | 1 | 0.5% | |
85742.195 | 1 | 0.5% |
Distinct count | 62 |
---|---|
Unique (%) | 100.0% |
Missing | 146 |
Missing (%) | 70.2% |
Infinite | 0 |
Infinite (%) | 0.0% |
Mean | 28826.0 |
---|---|
Minimum | 28.0 |
Maximum | 72814.0 |
Zeros | 0 |
Zeros (%) | 0.0% |
Memory size | 1.8 KiB |
Quantile statistics
Minimum | 28 |
---|---|
5-th percentile | 39.5 |
Q1 | 1607.5 |
median | 20701.5 |
Q3 | 56925.75 |
95-th percentile | 71229.45 |
Maximum | 72814 |
Range | 72786 |
Interquartile range (IQR) | 55318.25 |
Descriptive statistics
Standard deviation | 27386.31517 |
---|---|
Coefficient of variation (CV) | 0.9500560318 |
Kurtosis | -1.522122967 |
Mean | 28826 |
Median Absolute Deviation (MAD) | 20574 |
Skewness | 0.3736451882 |
Sum | 1787212 |
Variance | 750010258.8 |
Histogram with fixed size bins (bins=10)
Value | Count | Frequency (%) | |
67910 | 1 | 0.5% | |
7977 | 1 | 0.5% | |
61644 | 1 | 0.5% | |
15962 | 1 | 0.5% | |
60181 | 1 | 0.5% | |
67017 | 1 | 0.5% | |
3918 | 1 | 0.5% | |
1477 | 1 | 0.5% | |
52292 | 1 | 0.5% | |
62901 | 1 | 0.5% | |
18014 | 1 | 0.5% | |
70535 | 1 | 0.5% | |
55539 | 1 | 0.5% | |
32930 | 1 | 0.5% | |
57388 | 1 | 0.5% | |
50001 | 1 | 0.5% | |
22699 | 1 | 0.5% | |
614 | 1 | 0.5% | |
463 | 1 | 0.5% | |
275 | 1 | 0.5% | |
214 | 1 | 0.5% | |
135 | 1 | 0.5% | |
120 | 1 | 0.5% | |
101 | 1 | 0.5% | |
58 | 1 | 0.5% | |
Other values (37) | 37 | 17.8% | |
(Missing) | 146 | 70.2% |
Value | Count | Frequency (%) | |
28 | 1 | 0.5% | |
30 | 1 | 0.5% | |
36 | 1 | 0.5% | |
39 | 1 | 0.5% | |
49 | 1 | 0.5% | |
58 | 1 | 0.5% | |
101 | 1 | 0.5% | |
120 | 1 | 0.5% | |
135 | 1 | 0.5% | |
214 | 1 | 0.5% |
Value | Count | Frequency (%) | |
72814 | 1 | 0.5% | |
72362 | 1 | 0.5% | |
71857 | 1 | 0.5% | |
71266 | 1 | 0.5% | |
70535 | 1 | 0.5% | |
69755 | 1 | 0.5% | |
68798 | 1 | 0.5% | |
67910 | 1 | 0.5% | |
67017 | 1 | 0.5% | |
65660 | 1 | 0.5% |
Pearson's r
The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.
Spearman's ρ
The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.
Kendall's τ
Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.
Phik (φk)
Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.First rows
df_index | Predicted Recoveries | Recoveries | |
---|---|---|---|
0 | 2020-01-22 | 28.00 | 28.0 |
1 | 2020-01-23 | 30.00 | 30.0 |
2 | 2020-01-24 | 36.00 | 36.0 |
3 | 2020-01-25 | 39.00 | 39.0 |
4 | 2020-01-26 | 49.00 | 49.0 |
5 | 2020-01-27 | 58.00 | 58.0 |
6 | 2020-01-28 | 101.00 | 101.0 |
7 | 2020-01-29 | 120.00 | 120.0 |
8 | 2020-01-30 | 135.00 | 135.0 |
9 | 2020-01-31 | 163.91 | 214.0 |
Last rows
df_index | Predicted Recoveries | Recoveries | |
---|---|---|---|
198 | 2020-08-07 | 85742.194997 | NaN |
199 | 2020-08-08 | 85864.471347 | NaN |
200 | 2020-08-09 | 85989.808353 | NaN |
201 | 2020-08-10 | 86118.411768 | NaN |
202 | 2020-08-11 | 86249.072944 | NaN |
203 | 2020-08-12 | 86378.567838 | NaN |
204 | 2020-08-13 | 86506.488090 | NaN |
205 | 2020-08-14 | 86633.993923 | NaN |
206 | 2020-08-15 | 86761.814349 | NaN |
207 | 2020-08-16 | 86889.087344 | NaN |