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Generates profile reports from a pandas DataFrame. The pandas df.describe() function is great but a little basic for serious exploratory data analysis. pandas_profiling extends the pandas DataFrame with df.profile_report() for quick data analysis.

For each column the following statistics - if relevant for the column type - are presented in an interactive HTML report:

  • Type inference: detect the types of columns in a dataframe.

  • Essentials: type, unique values, missing values

  • Quantile statistics like minimum value, Q1, median, Q3, maximum, range, interquartile range

  • Descriptive statistics like mean, mode, standard deviation, sum, median absolute deviation, coefficient of variation, kurtosis, skewness

  • Most frequent values

  • Histograms

  • Correlations highlighting of highly correlated variables, Spearman, Pearson and Kendall matrices

  • Missing values matrix, count, heatmap and dendrogram of missing values

  • Duplicate rows Lists the most occurring duplicate rows

  • Text analysis learn about categories (Uppercase, Space), scripts (Latin, Cyrillic) and blocks (ASCII) of text data