Introduction
Series
What DataFrames are
DataFrame columns
DataFrame rows
Filtering rows and columns
Filtering data frames
Sorting rows
Summary
31. Summary

Instruction

Time to wrap things up! In this part of the course, we talked about DataFrames, the basic data structure of the pandas library. Let's recap what we learned.

  • pd.read_csv('file.csv') creates a new DataFrame based on file.csv.
  • To access a single column, use:

    dataframe['column_name']
  • To create a new column, use:

    dataframe['new_column'] = ...
  • To drop a column, use:

    dataframe.drop('column_name', axis=1)
  • To select a row based on its integer location, use:

    dataframe.iloc[2]
  • To select a row based on the current index, use:

    dataframe.loc[index_value]
  • To filter rows in a DataFrame using the index slice notation use:

    dataframe[start_index:end_index]

    The start_index is inclusive, the end_index is exclusive.

  • To filter rows by index and columns by name at the same time, use:

    dataframe.loc[index_value, 'column name']
  • To set a column as the index, use:

    dataframe.set_index('column_name')
  • To reset the index, use:

    dataframe.reset_index(drop=True)
  • To sort rows, use:

    dataframe.sort_values(by='column_name')

Okay, how about a short quiz now?

Exercise

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