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Only a selective number of columns were used in the analysis (Some were not necessary therefore not used)
To remove all columns but the ones listed, a simple iteration through the DataFrame column was used and all unwanted columns were dropped
Doing this saves processing power while referring to the dataframe or implementing the dataframe for analysis
The data included a daily report of all countries included, only the United States data was used
To remove all other countries data the DataFrame was reshaped to allow the location to be the index and it was then shortned used the loc() method.
The data was then indexed by date using the set_index() method and date_range() function
Although the dataset did have a date column, using pandas date_range() makes it easier to graph the dates in set intervals rather than listing all the days in their original format
The location and date column were then dropped from the dataframe as they were not needed
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