Is it possible to append Series to rows of DataFrame without making a list first?

I have some data I'm trying to organize into a DataFrame in Pandas. I was trying to make each row a Series and append it to the DataFrame. I found a way to do it by appending the Series to an empty list and then converting the list of Series to a DataFrame

e.g. DF = DataFrame([series1,series2],columns=series1.index)

This list to DataFrame step seems to be excessive. I've checked out a few examples on here but none of the Series preserved the Index labels from the Series to use them as column labels.

My long way where columns are id_names and rows are type_names:

Is it possible to append Series to rows of DataFrame without making a list first?

#!/usr/bin/python

DF = DataFrame()
for sample,data in D_sample_data.items():
    SR_row = pd.Series(data.D_key_value)
    DF.append(SR_row)
DF.head()

TypeError: Can only append a Series if ignore_index=True or if the Series has a name

Then I tried

DF = DataFrame()
for sample,data in D_sample_data.items():
    SR_row = pd.Series(data.D_key_value,name=sample)
    DF.append(SR_row)
DF.head()

Empty DataFrame

Tried Insert a row to pandas dataframe Still getting an empty dataframe :/

I am trying to get the Series to be the rows, where the index of the Series becomes the column labels of the DataFrame

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.