Pandas

Basic information about dataframe df.info() #basic information about dataframe len(df.index) #rethrn the number of rows (data) df.count() #return the number of values which are non-NaN on each column df.head() df.tail() Count the data in a column In this example, the column is “Product”. df["Product"].value_counts() unique values to series. df["Product"].unique() # the type numpy.ndarray check distrivution in graph # Check the data distribution # The column is Score ax = df["Score"]value_counts().plot(kind='bar') fig = ax.