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

Question

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

User · Accepted Answer

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()

User · Answer

Try using this command  See the example given below     df loc len df       Product 9  99 9 99 8 88 1 11   df

User · Answer

This would work as well  df   pd DataFrame   new line   pd Series   A2M   4 059   A2ML1   4 28   name  HCC1419   df   df append new line  ignore index False   The name in the Series will be the index in the dataframe  ignore index False is the important flag in this case

User · Answer

Something like this could work     mydf loc  newindex     myseries   Here is an example where I used it     stats   df   bp prob    ICD9 prob    meds prob    regex prob    describe    stats Out 32              bp prob   ICD9 prob   meds prob  regex prob count  171 000000  171 000000  171 000000  171 000000 mean     0 179946    0 059071    0 067020    0 126812 std      0 271546    0 142681    0 152560    0 207014 min      0 000000    0 000000    0 000000    0 000000 25       0 000000    0 000000    0 000000    0 000000 50       0 000000    0 000000    0 000000    0 013116 75       0 309019    0 065248    0 066667    0 192954 max      1 000000    1 000000    1 000000    1 000000  medians   df   bp prob    ICD9 prob    meds prob    regex prob    median    stats loc  median     medians  stats Out 36               bp prob   ICD9 prob   meds prob  regex prob count   171 000000  171 000000  171 000000  171 000000 mean      0 179946    0 059071    0 067020    0 126812 std       0 271546    0 142681    0 152560    0 207014 min       0 000000    0 000000    0 000000    0 000000 25        0 000000    0 000000    0 000000    0 000000 50        0 000000    0 000000    0 000000    0 013116 75        0 309019    0 065248    0 066667    0 192954 max       1 000000    1 000000    1 000000    1 000000 median    0 000000    0 000000    0 000000    0 013116

User · Answer

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

User · Answer

Convert the series to a dataframe and transpose it  then append normally   srs   srs to frame   T df   df append srs

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

Examples related to python

Examples related to pandas

Examples related to machine-learning

Examples related to dataframe

Examples related to series