Dataset statistics
Number of variables | 2 |
---|---|
Number of observations | 361 |
Missing cells | 0 |
Missing cells (%) | 0.0% |
Duplicate rows | 0 |
Duplicate rows (%) | 0.0% |
Total size in memory | 5.8 KiB |
Average record size in memory | 16.4 B |
Variable types
DATE | 1 |
---|---|
NUM | 1 |
Reproduction
Analysis started | 2020-02-14 00:01:34.856147 |
---|---|
Analysis finished | 2020-02-14 00:01:35.713906 |
Version | pandas-profiling v2.5.0 |
Command line | pandas_profiling --config_file config.yaml [YOUR_FILE.csv] |
Download configuration | config.yaml |
Distinct count | 361 |
---|---|
Unique (%) | 100.0% |
Missing | 0 |
Missing (%) | 0.0% |
Memory size | 2.9 KiB |
Minimum | 1990-01-01 00:00:00 |
---|---|
Maximum | 2020-01-01 00:00:00 |
Histogram
Distinct count | 361 |
---|---|
Unique (%) | 100.0% |
Missing | 0 |
Missing (%) | 0.0% |
Infinite | 0 |
Infinite (%) | 0.0% |
Mean | 1.1942046709516831 |
---|---|
Minimum | 0.56105 |
Maximum | 2.17254761904762 |
Zeros | 0 |
Zeros (%) | 0.0% |
Memory size | 2.9 KiB |
Quantile statistics
Minimum | 0.56105 |
---|---|
5-th percentile | 0.7371818182 |
Q1 | 0.9244318182 |
median | 1.15725 |
Q3 | 1.428714286 |
95-th percentile | 1.86452381 |
Maximum | 2.172547619 |
Range | 1.611497619 |
Interquartile range (IQR) | 0.5042824675 |
Descriptive statistics
Standard deviation | 0.3473087284 |
---|---|
Coefficient of variation (CV) | 0.2908284793 |
Kurtosis | -0.400216634 |
Mean | 1.194204671 |
Median Absolute Deviation (MAD) | 0.2839333612 |
Skewness | 0.5405907172 |
Sum | 431.1078862 |
Variance | 0.1206233528 |
Histogram with fixed size bins (bins=10)
Histogram with variable size bins (bins=[0.56105 0.73767045 1.46855323 2.02435714 2.17254762], "bayesian blocks" binning strategy used)
Value | Count | Frequency (%) | |
1.746478261 | 1 | 0.3% | |
1.084357143 | 1 | 0.3% | |
1.398880952 | 1 | 0.3% | |
1.448368421 | 1 | 0.3% | |
1.180863636 | 1 | 0.3% | |
1.86452381 | 1 | 0.3% | |
1.527738095 | 1 | 0.3% | |
1.374657895 | 1 | 0.3% | |
1.014954545 | 1 | 0.3% | |
1.388818182 | 1 | 0.3% | |
Other values (351) | 351 | 97.2% |
Value | Count | Frequency (%) | |
0.56105 | 1 | 0.3% | |
0.5766190476 | 1 | 0.3% | |
0.594547619 | 1 | 0.3% | |
0.6096842105 | 1 | 0.3% | |
0.6121304348 | 1 | 0.3% |
Value | Count | Frequency (%) | |
2.172547619 | 1 | 0.3% | |
2.03602381 | 1 | 0.3% | |
2.012690476 | 1 | 0.3% | |
2.012275 | 1 | 0.3% | |
2.00325 | 1 | 0.3% |
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.
First rows
DATE | PORANGUSDM | |
---|---|---|
0 | 1990-01-01 | 1.913636 |
1 | 1990-02-01 | 1.940289 |
2 | 1990-03-01 | 1.922636 |
3 | 1990-04-01 | 1.960125 |
4 | 1990-05-01 | 1.949477 |
5 | 1990-06-01 | 1.864524 |
6 | 1990-07-01 | 1.833381 |
7 | 1990-08-01 | 1.724717 |
8 | 1990-09-01 | 1.445579 |
9 | 1990-10-01 | 1.230826 |
Last rows
DATE | PORANGUSDM | |
---|---|---|
351 | 2019-04-01 | 1.084357 |
352 | 2019-05-01 | 0.986045 |
353 | 2019-06-01 | 1.027250 |
354 | 2019-07-01 | 1.014955 |
355 | 2019-08-01 | 0.993318 |
356 | 2019-09-01 | 1.006300 |
357 | 2019-10-01 | 0.984370 |
358 | 2019-11-01 | 0.981600 |
359 | 2019-12-01 | 0.975905 |
360 | 2020-01-01 | 0.969095 |