tut01-lesson2-create_party_table.py

    def create_party_table(self):
        # Panda Data Frame - Table of Tweeter Users per Party
        # https://stackoverflow.com/questions/48909110/python-pandas-mean-and-sum-groupby-on-different-columns-at-the-same-time
        panda_data = { "Party": self.__col_party,
                       "PartyCount": self.__col_party, # Duplicate Party column for the counting
                       "FollowersCount": self.__col_followers_count,
                       "FriendsCount": self.__col_friends_count
                       }
        df = DataFrame(panda_data , index=self.__labels)
        # We use the as_index parameter, so that Party will also be a column of the data frame
        df = df.groupby(["Party"], as_index=False).agg({'PartyCount':'count','FollowersCount':'sum', 'FriendsCount': 'sum'})
        df = df.sort_values(['FollowersCount'], ascending=[0])
        print(df)
        # Create a Plotly Table
        trace = go.Table(
            header = dict(values=list(df.columns)),
            cells = dict(values=[df.Party,  df.PartyCount, df.FollowersCount, df.FriendsCount]))
        data = [trace]
        py.plot(data, filename=self.__country_code+'-tw-party-list')
        return df