Append list to pandas DataFrame as new row with index
Either assign in-place with loc
:
df.loc['two'] = [4, 5, 6]
# df.loc['two', :] = [4, 5, 6]
df
A B C
one 1 2 3
two 4 5 6
Or, use df.append
with the second argument being a Series
object having appropriate index and name:
s = pd.Series(dict(zip(df.columns, [4, 5, 6])).rename('two'))
df2 = df.append(s)
df2
A B C
one 1 2 3
two 4 5 6
If you are appending to a DataFrame without an index (i.e., having a numeric index), you can use loc
after finding the max of the index and incrementing by 1:
df4 = pd.DataFrame(np.array([1,2,3]).reshape(1,3), columns=list('ABC'))
df4
A B C
0 1 2 3
df4.loc[df4.index.max() + 1, :] = [4, 5, 6]
df4
A B C
0 1.0 2.0 3.0
1 4.0 5.0 6.0
Or, using append
with ignore_index=True
:
df4.append(pd.Series(dict(zip(df4.columns, [4, 5, 6]))), ignore_index=True)
A B C
0 1 2 3
1 4 5 6
JFerro
NLP with Spacy Pandas Networkx ipywidgets, ipysheets, voila, ipyvuewtify in Jupyter Hub environement NLP for patent literature. Feature extraction. EPC & PCT compliance based on NLP techniques. Interested in Machine learning for information extraction in EN, FR, DE, NL, SP, PT languages.
Updated on September 16, 2020Comments
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JFerro over 3 years
Despite of the numerous stack overflow questions on appending data to a dataframe I could not really find an answer to the following. I am looking for a straight forward solution to append a list as last row of a dataframe. Imagine I have a simple dataframe:
indexlist=['one'] columnList=list('ABC') values=np.array([1,2,3]) # take care, the values array is a 3x1 size array. # row has to be 1x3 so we have to reshape it values=values.reshape(1,3) df3=pd.DataFrame(values,index=indexlist,columns=columnList) print(df3) A B C one 1 2 3
After some operations I get the following list:
listtwo=[4,5,6]
I want to append it at the end of the dataframe. I change that list into a series:
oseries=pd.Series(listtwo) print(type(oseries)) oseries.name="two"
now, this does not work:
df3.append(oseries)
since it gives:
A B C 0 1 2 one 1.0 2.0 3.0 NaN NaN NaN two NaN NaN NaN 5.0 6.0 7.0
I would like to have the values under A B and C.
I also tried:
df3.append(oseries, columns=list('ABC')) *** not working *** df3.append(oseries, ignore_index=True) *** working but wrong result df3.append(oseries, ignore_index=False) *** working but wrong result df3.loc[oseries.name]=oseries adds a row with NaN values
what I am looking for is a) how can I add a list to a particular index name b) how can I simple add a row of values out of a list even if I don't have a name for index (leave it empty)
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JFerro over 5 yearsThanks. What if I am not using an index. Simply adding rows of data for later processing. Why is this not working:? df4=pd.DataFrame(np.array([1,2,3]).reshape(1,3),columns=list('ABC')) newlist=[5,6,7] df4.append(newlist) be aware the dataframe was created on purpose without index.
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cs95 over 5 years@Berlines Simply because
df4.append
was not intended to work with lists directly. If you are appending a single row, you must either supply a pd.Series object (which you did and noticed there was an issue aligning the columns), or use loc and assign in-place. -
cs95 over 5 years@Berlines Quite so.