Dynamically Add Rows to DataFrame

Question

Let's say I have an empty dataframe, already set up with columns, but no rows. I'm scraping some data from the web so let's say I need to add an index '2176' to the empty dataframe. How could I automatically add this row to the database when I try to assign it? Is this even pandas purpose or should I use something else?

Answer 1

As an alternative to .loc, you might want to consider at. Using @NickBraunagel's example:

df = pd.DataFrame(columns=['foo1','foo2'])

Then

df.at['2716', 'foo1'] = 10

yields

     foo1 foo2
2716   10  NaN

Timings are quite different:

# @NickBraunagel's solution
%timeit df.loc['2716', 'foo1'] = 10
1000 loops, best of 3: 212 µs per loop

# the at solution
%timeit df.at['2716', 'foo1'] = 10
100000 loops, best of 3: 12.5 µs per loop

If you want to add several column entries at the same time, you can do:

d = {'foo1': 20, 'foo2': 10}
df.at['1234', :] = d

yielding

     foo1 foo2
2716   10  NaN
1234   20   10

However, make sure to always add the same datatype to avoid errors or other undesired effects as explained here.