<p>早于1.1.5版本的交叉连接代码</p>
<pre><code>#creating a df with all unique countries and iso_codes
#creating a new table with all the dates in the original dataframe
countries = animation_covid_df.loc[:, ['country', 'iso_code']].drop_duplicates()
dates_df = animation_covid_df.loc[:, ['date']].drop_duplicates()
#creating an index called row number to later merge the dates table with the countries table on
dates_df['row_number'] = dates_df.reset_index().index
number_of_dates = dates_df.max() #shows the number of dates or rows in the the dates table
#creating an equivalent number of rows for each country as there are dates in the dates_df
indexed_country = countries.append([countries]*number_of_dates[1],ignore_index=True)
indexed_country = indexed_country.sort_values(['country', 'iso_code'], ascending=True)
#creating a new column called 'row_number' to join the indexed_country df with the dates_df
indexed_country['row_number'] = indexed_country.groupby(['country', 'iso_code']).cumcount()+1
#merging all the indexed countries with all the possible dates on the row number
indexed_country_date_df = indexed_country.merge(dates_df, on='row_number', how='left', suffixes=('_1', '_2'))
#setting the 'date' column in both tables to datetime so they can be merged on
animation_covid_df['date'] = pd.to_datetime(animation_covid_df['date'])
indexed_country_date_df['date'] = pd.to_datetime(indexed_country_date_df['date'])
</code></pre>
