python - How to add an extra row to a pandas dataframe

Question

This question already has answers here:

Create pandas Dataframe by appending one row at a time (31 answers)

Closed 4 years ago.

If I have an empty dataframe as such:

columns = ['Date', 'Name', 'Action','ID']
df = pd.DataFrame(columns=columns) 

is there a way to append a new row to this newly created dataframe? Currently I have to create a dictionary, populate it, then append the dictionary to the dataframe at the end. Is there a more direct way?

Answer 1

Upcoming pandas 0.13 version will allow to add rows through loc on non existing index data. However, be aware that under the hood, this creates a copy of the entire DataFrame so it is not an efficient operation.

Description is here and this new feature is called Setting With Enlargement.

Answer 2

Try this:

df.loc[len(df)]=['8/19/2014','Jun','Fly','98765'] 

Warning: this method works only if there are no "holes" in the index. For example, suppose you have a dataframe with three rows, with indices 0, 1, and 3 (for example, because you deleted row number 2). Then, len(df) = 3, so by the above command does not add a new row - it overrides row number 3.

Answer 3

A different approach that I found ugly compared to the classic dict+append, but that works:

df = df.T

df[0] = ['1/1/2013', 'Smith','test',123]

df = df.T

df
Out[6]: 
       Date   Name Action   ID
0  1/1/2013  Smith   test  123