Function to plot categorical data

plot_categorical.py

def plot_categorical(df: pd.DataFrame , col:str):
    """
    Function to plot the categorical data on piechart using Plotly
    @Args:
      df: pandas data frame
      col: A string column name within pandas data frame to plot
      
    Return:
      No object return, only visualization
    """
    value_ = df[col].value_counts().values
    idx_ = df[col].value_counts().index
    
    trace = [{'values': value_,
              'labels': idx_,
              'name': col,
              'hoverinfo': 'label+value+name',
              'hole': 0.4,
              'type': 'pie'
             }]

    layout = {'title': '<b>%s</b> categorical distribution' % col,
              'paper_bgcolor': '#e8e8e8',
              'plot_bgcolor': '#e8e8e8',
              'autosize': False,
              'width': 800,
              'height': 400,
              'annotations': [{'text' : '<b>%s</b>' % col,
                              'font': {'size': 11,
                                       'color': 'black'},
                              'x': 0.5,
                              'y': 0.5,
                              'showarrow': False
                              }]
             }
    py.iplot({'data': trace, 'layout': layout})
    

le_10_val_col = []
mt_10_val_col = []
obj_val_col = []
for col in data_df.columns:
    if (len(data_df[col].unique()) <= 10) & (data_df[col].dtypes == 'int64'):
        le_10_val_col.append(col)
    elif (len(data_df[col].unique()) > 10) & (data_df[col].dtypes == 'int64'):
        mt_10_val_col.append(col)
    elif data_df[col].dtypes == 'O':
        obj_val_col.append(col)
        
for i in obj_val_col:
    plot_categorical(data_df, i)