Is it possible to append Series to rows of DataFrame without making a list first?
Maybe an easier way would be to add the pandas.Series
into the pandas.DataFrame
with ignore_index=True
argument to DataFrame.append()
. Example -
DF = DataFrame()
for sample,data in D_sample_data.items():
SR_row = pd.Series(data.D_key_value)
DF = DF.append(SR_row,ignore_index=True)
Demo -
In [1]: import pandas as pd
In [2]: df = pd.DataFrame([[1,2],[3,4]],columns=['A','B'])
In [3]: df
Out[3]:
A B
0 1 2
1 3 4
In [5]: s = pd.Series([5,6],index=['A','B'])
In [6]: s
Out[6]:
A 5
B 6
dtype: int64
In [36]: df.append(s,ignore_index=True)
Out[36]:
A B
0 1 2
1 3 4
2 5 6
Another issue in your code is that DataFrame.append()
is not in-place, it returns the appended dataframe, you would need to assign it back to your original dataframe for it to work. Example -
DF = DF.append(SR_row,ignore_index=True)
To preserve the labels, you can use your solution to include name for the series along with assigning the appended DataFrame back to DF
. Example -
DF = DataFrame()
for sample,data in D_sample_data.items():
SR_row = pd.Series(data.D_key_value,name=sample)
DF = DF.append(SR_row)
DF.head()
DataFrame.append
does not modify the DataFrame in place. You need to do df = df.append(...)
if you want to reassign it back to the original variable.