Good alternative to Pandas .append() method, now that it is being deprecated?

Question

I use the following method a lot to append a single row to a dataframe. One thing I really like about it is that it allows you to append a simple dict object. For example:

# Creating an empty dataframe
df = pd.DataFrame(columns=['a', 'b'])

# Appending a row
df = df.append({ 'a': 1, 'b': 2 }, ignore_index=True)

Again, what I like most about this is that the code is very clean and requires very few lines. Now I suppose the recommended alternative is:

# Create the new row as its own dataframe
df_new_row = pd.DataFrame({ 'a': [1], 'b': [2] })
df = pd.concat([df, df_new_row])

So what was one line of code before is now two lines with a throwaway variable and extra cruft where I create the new dataframe. :( Is there a good way to do this that just uses a dict like I have in the past (that is not deprecated)?

Answer 1

Create a list with your dictionaries, if they are needed, and then create a new dataframe with df = pd.DataFrame.from_records(your_list). List's "append" method are very efficient and won't be ever deprecated. Dataframes on the other hand, frequently have to be recreated and all data copied over on appends, due to their design - that is why they deprecated the method

Answer 2

I also like the append method. But you can do it in one line with a list of dicts

df = pd.concat([df, pd.DataFrame.from_records([{ 'a': 1, 'b': 2 }])])

or using loc and tuples for values on DataFrames with incremenal ascending indexes

df.loc[len(df), ['a','b']] = 1, 2

or maybe

df.loc[len(df), df.columns] = 3, 4

Answer 3

This have already good answare, but I just wanted to append something at the end here as I didnt find it :) If you are appending a DF to a DF and want to use concat this is the way I found:

original with append

   outputxlsx = outputxlsx.append( df, ignore_index=True)

concat

   outputxlsx = pd.concat([outputxlsx, pd.DataFrame.from_records(df)])