I have a text file which I read into a pandas DataFrame.
File A:
2009,7,1,3,101,13.03,89.33,0.6,287.69,0
2009,7,1,6,102,19.3,55,1,288.67,0
2009,7,1,9,103,22.33,39.67,1,289.6,0
2009,7,1,12,104,21.97,41,1,295.68,0
Read this into a DataFrame
>>> import pandas as pd
>>> from datetime import datetime as dtdt
>>> par3 = lambda x: dtdt.strptime(x, '%Y %m %d %H')
>>> df3=pd.read_csv('fileA.txt',header=None,parse_dates={'Date': [0,1,2,3]}, date_parser=par3, index_col='Date')
>>> df3
4 5 6 7 8 9
Date
2009-07-01 03:00:00 101 13.03 89.33 0.6 287.69 0
2009-07-01 06:00:00 102 19.30 55.00 1.0 288.67 0
2009-07-01 09:00:00 103 22.33 39.67 1.0 289.60 0
2009-07-01 12:00:00 104 21.97 41.00 1.0 295.68 0
Then, I have new data to be appended into df3 as a new row
bb = '2009-07-01 15:00:00'
cc = '105 18.11 44.55 1.2 300.12 0'
Question how do I append this new row to get
>>> new_df3
4 5 6 7 8 9
Date
2009-07-01 03:00:00 101 13.03 89.33 0.6 287.69 0
2009-07-01 06:00:00 102 19.30 55.00 1.0 288.67 0
2009-07-01 09:00:00 103 22.33 39.67 1.0 289.60 0
2009-07-01 12:00:00 104 21.97 41.00 1.0 295.68 0
2009-07-01 15:00:00 105 18.11 44.55 1.2 300.12 0
This How to append dictionary to DataFrame as a row? did not work in my case, I get either messy results or error messages.
I am aware of the docs https://pandas.pydata.org/pandas-docs/stable/user_guide/text.html, (join): https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.join.html#pandas.DataFrame.join (merge): https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.merge.html#pandas.DataFrame.merge but my head already has pretty much exploded. Solution would be very much appreciated.
row = {"Date": bb}row.update(dict(zip(range(4, 9), cc.split())); df3.append(row)?