Python: Create empty pandas dataframe and add elements to its columns dynamically

Question

I am running a for loop for each of 12 months. For each month I get bunch of dates in random order over various years in history. I also have corresponding temperature data on those dates. e.g. if I am in month January, of loop all dates and temperature I get from history are for January only.

I want to start with empty pandas dataframe with two columns namely 'Dates' and 'Temperature'. As the loop progresses I want to add the dates from another month and corresponding data to the 'Temperature' column.

After my dataframe is ready I want to finally use the 'Dates'column as index to order the 'Temperature' history available so that I have correct historical sorted dates with their temperatures.

I have thought about using numpy array and storing dates and data in two separate arrays; sort the dates and then sort the temperature using some kind of index. I believe using pandas pivot table feature it will be better implemented in pandas.

Ajay Jadhav · Accepted Answer · 2016-05-30 11:46:59Z

1

@Zanam Pls refer this syntax. I think your question is similar to this answer

 df = DataFrame(columns=('lib', 'qty1', 'qty2'))
 for i in range(5):
    df.loc[i] = [randint(-1,1) for n in range(3)]

 print(df)

     lib  qty1  qty2
 0    0     0    -1
 1   -1    -1     1
 2    1    -1     1
 3    0     0     0
 4    1    -1    -1

 [5 rows x 3 columns]

answered May 30, 2016 at 11:46

Ajay Jadhav

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