Introduction

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