Writing single CSV header with pandas

Question

I'm parsing data into lists and using pandas to frame and write to an CSV file. First my data is taken into a set where inv, name, and date are all lists with numerous entries. Then I use concat to concatenate each iteration through the datasets I parse through to a CSV file like so:

counter = True
data = {'Invention': inv, 'Inventor': name, 'Date': date}

if counter is True:
  df = pd.DataFrame(data)
  df = df[['Invetion', 'Inventor', 'Date']]

else:
  df = pd.concat([df, pd.DataFrame(data)])
  df = df[['Invention', 'Inventor', 'Date']]

  with open('./new.csv', 'a', encoding = utf-8) as f:
    if counter is True:
      df.to_csv(f, index = False, header = True)
    else:
      df.to_csv(f, index = False, header = False)

counter = False

The counter = True statement resides outside of my iteration loop for all the data I'm parsing so it's not overwriting every time.

So this means it only runs once through my data to grab the first df set then concats it thereafter. The problem is that even though counter is only True the first round and works for my first if-statement for df it does not work for my writing to file.

What happens is that the header is written over and over again - regardless to the fact that counter is only True once. When I swap the header = False for when counter is True then it never writes the header.

I think this is because of the concatenation of df holding onto the header somehow but other than that I cannot figure out the logic error.

Is there perhaps another way I could also write a header once and only once to the same CSV file?

Answer 1

It's hard to tell what might be going wrong without seeing the rest of the code. I've developed some test data and logic that works; you can adapt it to fit your needs.

Please try this:

import pandas as pd

early_inventions = ['wheel', 'fire', 'bronze']
later_inventions = ['automobile', 'computer', 'rocket']

early_names = ['a', 'b', 'c']
later_names = ['z', 'y', 'x']

early_dates = ['2000-01-01', '2001-10-01', '2002-03-10']
later_dates = ['2010-01-28', '2011-10-10', '2012-12-31']

early_data = {'Invention': early_inventions,
    'Inventor': early_names,
    'Date': early_dates}

later_data = {'Invention': later_inventions,
    'Inventor': later_names,
    'Date': later_dates}

datasets = [early_data, later_data]

columns = ['Invention', 'Inventor', 'Date']
header = True
for dataset in datasets:
    df = pd.DataFrame(dataset)
    df = df[columns]
    mode = 'w' if header else 'a'
    df.to_csv('./new.csv', encoding='utf-8', mode=mode, header=header, index=False)
    header = False

Alternatively, you can concatenate all of the data in the loop and write out the dataframe at the end:

df = pd.DataFrame(columns=columns)
for dataset in datasets:
    df = pd.concat([df, pd.DataFrame(dataset)])
    df = df[columns]
df.to_csv('./new.csv', encoding='utf-8', index=False)

If your code cannot be made to conform to this API, you can forego writing the header in to_csv altogether. You can detect whether the output file exists and write the header to it first if it does not:

import os

fn = './new.csv'
if not os.path.exists(fn):
    with open(fn, mode='w', encoding='utf-8') as f:
        f.write(','.join(columns) + '\n')
# Now append the dataframe without a header
df.to_csv(fn, encoding='utf-8', mode='a', header=False, index=False)