Toolboxes
Statistics and Machine Learning Toolbox → scipy.stats + pandas
Statistical distributions, hypothesis testing, and regression. Maps to scipy.stats and pandas.
Install
pip install scipy pandas| MATLAB | Python | Note |
|---|---|---|
| normpdf(x, mu, sig) | stats.norm.pdf(x, mu, sig) | |
| normcdf(x, mu, sig) | stats.norm.cdf(x, mu, sig) | |
| norminv(p, mu, sig) | stats.norm.ppf(p, mu, sig) | |
| normrnd(mu, sig, m, n) | np.random.normal(mu, sig, (m, n)) | |
| ttest(x) | stats.ttest_1samp(x, 0) | |
| ttest2(x, y) | stats.ttest_ind(x, y) | |
| anova1(data) | stats.f_oneway(*groups) | |
| chi2test(x) | stats.chi2_contingency(x) | |
| corrcoef(X) | np.corrcoef(X) | |
| cov(X) | np.cov(X) | |
| polyfit(x, y, n) | np.polyfit(x, y, n) | |
| polyval(p, x) | np.polyval(p, x) | |
| tabulate(x) | pd.value_counts(x) | |
| quantile(x, p) | np.quantile(x, p) | |
| prctile(x, p) | np.percentile(x, p) |
The converter automatically detects Statistics functions and adds the correct imports.
Try the converter