[FIXED] Pandas DF output format for a text file

Issue

How do I set a column format for a Pandas data frame, when I am printing it to a file?

Or where can I find documentation on how to do this?

All I am finding is information relating to how to format the DF for visualization, but not in regards of printing the DF in a format.

def print_Report(dataframe, originalFile, newFile):
 
  pageNum = 1
  start_row = 0
  end_row = 49
  max_row = len(dataframe.index)
  ln4pad = 123
  padding = ' '

  #Grabs lines 5-17 of original report file via slice
  originalHeader = retrieveHeader(originalFile)

  while start_row < max_row:

    with open(newFile, 'a') as f:

      #Writes Lines 1-4 of header
      ln4 = 'Page   ' + str(pageNum)
      f.write(f'\n1\n\n\n{ln4.rjust(ln4pad, padding)}\n\n'

      #Writes Lines 5-17 of header
      for item in originalHeader:
        f.write(item)

      #Writing DF to file
      dfAsString = (dataframe.iloc[start_row:end_row]).to_string(index=False, header=False)
      f.write(dfAsString)

      #Update Values
      pageNum += 1
      start_row += 49
      end_row   += 49

      if end_row > max_row
        end_row = max_row

I know the issue is inserting whitespace at the proper places, for the column formats. But I am just having trouble in finding how to do this.

Desired Format:

   EGG  HATCH TIME      EF    EB
   NO  HR MN SECONDS   SCAL  DCAL
    1  15 50 47.9293   67.1  21.6
    2  15 50 48.9824   67.1  21.6
    3  15 50 50.9657   67.2  20.4

Currently Printing as:

   EGG  HATCH TIME      EF    EB
   NO  HR MN SECONDS   SCAL  DCAL
 1 15 50 47.9293 67.1 21.6
 2 15 50 48.9824 67.1 21.6
 3 15 50 50.9657 67.2 20.4

Solution

You could use the col_space argument to to_string to align your columns:

dfAsString = (dataframe.iloc[start_row:end_row]).to_string(index=False, header=False, ,col_space=[5,3,2,7,6,5])

The output should then look like:

   NO  HR MN SECONDS   SCAL  DCAL
    1  15 50 47.9293   67.1  21.6
    2  15 50 48.9824   67.1  21.6
    3  15 50 50.9657   67.2  20.4

Answered By - Nick