How to fill up each element in a list to given columns of a dataframe?-CodePudding

Let's say I have a dataframe as shown.

I have a list now like [6,7,6]. How do I fill these to the my 3 desired columns i.e,[one,Two,Four] of dataframe? Notice that I have not given column 'three'. Final Dataframe should look like:

CodePudding user response：

you could do:

columnstobefilled = ["One","Two","Four"]
elementsfill = [6,3,6]
for column,element in zip(columnstobefilled,elementsfill):
    df[column] = element

CodePudding user response：

Since you want the list values to be in specific places you have to specify where each value should go. One way to include this is to use a key value pair object, a dictionary. Once you create that you can use append to include it as a row in your dataframe:

d = {'one':6,'Two':7,'Four':6}
df.append(d,ignore_index=True)

   one  Two  Three  Four
0  2.0  4.0    4.0   8.0
1  6.0  7.0    NaN   6.0

Dataset:

df = pd.DataFrame({'one':2,'Two':4,'Three':4,'Four':8},
                  index=[0])

CodePudding user response：

import pandas as pd
df = pd.DataFrame({'One':2, 'Two':4, 'Three':4, 'Four':8}, index=[0])
new_row = {'One':6, 'Two':7, 'Three':None, 'Four':6}
df.append(new_row, ignore_index=True)
print(df)

output:

   One  Two  Three  Four
0  2.0  4.0    4.0   8.0
1  6.0  7.0    NaN   6.0

CodePudding user response：

You can append a Series:

df = pd.DataFrame([[2, 4, 4, 8]],
                  columns=['One', 'Two', 'Three', 'Four'])

values = [6, 3, 6]
lst = ['One', 'Two', 'Four']

df = df.append(pd.Series(values, index=lst), ignore_index=True)

or a dict:

df = df.append(dict(zip(lst, values)), ignore_index=True)

output:

   One  Two  Three  Four
0  2.0  4.0    4.0   8.0
1  6.0  3.0    NaN   6.0