Adding Rows To Empty Dataframe With Columns
Solution 1:
There are two probably reasons your code is not operating as intended:
cereals.append(dt, ignore_index = True)
is not doing what you think it is. You're trying to append a series, not a DataFrame there.cereals.append(dt, ignore_index = True)
does not modifycereals
in place, so when you return it, you're returning an unchanged copy. An equivalent function would look like this:
--
>>>deffoo(a):... a + 1...return a...>>>foo(1)
1
I haven't tested this on my machine, but I think you're fixed solution would look like this:
def addRows(cereals, lines):
for i in np.arange(1,len(lines)):
data = parseLine(lines[i])
new_df = pd.DataFrame(data, columns=cereals.columns)
cereals = cereals.append(new_df, ignore_index=True)
return cereals
by the way.. I don't really know where lines is coming from, but right away I would at least modify it to look like this:
data = [parseLine(line) for line in lines]
cereals = cereals.append(pd.DataFrame(data, cereals.columns), ignore_index=True)
How to add an extra row to a pandas dataframe
You could also create a new DataFrame and just append that DataFrame to your existing one. E.g.
>>>import pandas as pd>>>empty_alph = pd.DataFrame(columns=['letter', 'index'])>>>alph_abc = pd.DataFrame([['a', 0], ['b', 1], ['c', 2]], columns=['letter', 'index'])>>>empty_alph.append(alph_abc)
letter index
0 a 0.0
1 b 1.0
2 c 2.0
As I noted in the link, you can also use the loc
method on a DataFrame:
>>>df = empty_alph.append(alph_abc)>>>df.loc[df.shape[0]] = ['d', 3] // df.shape[0] just finds next# in index
letter index
0 a 0.0
1 b 1.0
2 c 2.0
3 d 3.0
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