old_contents: import pandas as pd
  import argparse
  import os
  
  from pandas.tseries.holiday import USFederalHolidayCalendar as calendar
  
  
  def prepare_data(data_path):
      """Returns dataframe with features."""
  
      # Get data
      df = pd.read_csv(data_path)
  
      # Remove NaNs
      df = df.dropna()
  
      # Convert date to datetime
      df['date'] = pd.to_datetime(df.date)
  
      # Create and age variable
      df['age'] = df.index.astype('int')
  
      # Create a day of week field
      df['day'] = df.date.dt.dayofweek
  
      # Create a month of year field
      df['month'] = df.date.dt.month
  
      # Create a boolean for US federal holidays
      holidays = calendar().holidays(start=df.date.min(), end=df.date.max())
      df['holiday'] = df['date'].isin(holidays).apply(int)
  
      # Rearrange columns
      df = df[
          [
              'date',
              'count',
              'age',
              'month',
              'day',
              'holiday'
          ]
      ]
  
      # Create monthly dummies
      tmp = pd.get_dummies(df.month)
      tmp.columns = ['month' + str(value) for value in tmp.columns]
      df = pd.concat([df, tmp], axis=1)
  
      # Create daily dummies
      tmp = pd.get_dummies(df.day)
      tmp.columns = ['day' + str(value) for value in tmp.columns]
      df = pd.concat([df, tmp], axis=1)
  
      # Reset index
      df = df.reset_index(drop=True)
  
      return df
  
  
  def run():
      parser = argparse.ArgumentParser(description='Prepare data')
      parser.add_argument('--data_path',
                          default='raw/github_total_push_events_2011-2018.csv')
      parser.add_argument('--output_path',
                          default='processed/github_dau_2011-2018.pkl')
      args = parser.parse_args()
  
      # Get the data
      df = prepare_data(args.data_path)
  
      # Store data
      path = os.path.dirname(args.output_path)
      if not os.path.exists(path):
          os.makedirs(path)
      df.to_pickle(args.output_path)
  
  
  if __name__ == '__main__':
      run()
  
new_contents: import pandas as pd
  import argparse
  import os
  
  from pandas.tseries.holiday import USFederalHolidayCalendar as calendar
  
  
  def prepare_data(data_path):
      """Returns dataframe with features."""
  
      # Get data
      df = pd.read_csv(data_path)
  
      # Remove NaNs
      df = df.dropna()
  
      # Convert date to datetime
      df['date'] = pd.to_datetime(df.date)
  
      # Create and age variable
      df['age'] = df.index.astype('int')
  
      # Create a day of week field
      df['day'] = df.date.dt.dayofweek
  
      # Create a month of year field
      df['month'] = df.date.dt.month
  
      # Create a boolean for US federal holidays
      holidays = calendar().holidays(start=df.date.min(), end=df.date.max())
      df['holiday'] = df['date'].isin(holidays).apply(int)
  
      # Rearrange columns
      df = df[
          [
              'date',
              'count',
              'age',
              'month',
              'day',
              'holiday'
          ]
      ]
  
      # Create monthly dummies
      tmp = pd.get_dummies(df.month)
      tmp.columns = ['month' + str(value) for value in tmp.columns]
      df = pd.concat([df, tmp], axis=1)
  
      # Create daily dummies
      tmp = pd.get_dummies(df.day)
      tmp.columns = ['day' + str(value) for value in tmp.columns]
      df = pd.concat([df, tmp], axis=1)
  
      # Reset index
      df = df.reset_index(drop=True)
  
      return df
  
  
  def run():
      parser = argparse.ArgumentParser(description='Prepare data')
      parser.add_argument('--data_path',
                          default='raw/github_dau_2011-2018.csv')
      parser.add_argument('--output_path',
                          default='processed/github_dau_2011-2018.pkl')
      args = parser.parse_args()
  
      # Get the data
      df = prepare_data(args.data_path)
  
      # Store data
      path = os.path.dirname(args.output_path)
      if not os.path.exists(path):
          os.makedirs(path)
      df.to_pickle(args.output_path)
  
  
  if __name__ == '__main__':
      run()
  
subject: fix issue 61 wrong csv name