Convert pandas data frame to series

Question

I m somewhat new to pandas  I have a pandas data frame that is 1 row by 23 columns   I want to convert this into a series  I m wondering what the most pythonic way to do this is   I ve tried pd Series myResults  but it complains ValueError  cannot copy sequence with size 23 to array axis with dimension 1  It s not smart enough to realize it s still a  vector  in math terms    Thanks

User · Answer

You can retrieve the series through slicing your dataframe using one of these two methods:

http://pandas.pydata.org/pandas-docs/stable/generated/pandas.DataFrame.iloc.html http://pandas.pydata.org/pandas-docs/stable/generated/pandas.DataFrame.loc.html

import pandas as pd
import numpy as np
df = pd.DataFrame(data=np.random.randn(1,8))

series1=df.iloc[0,:]
type(series1)
pandas.core.series.Series

User · Answer

data   pd DataFrame   a   1 2 3 34   b   5 6 7 8    new data   pd melt data  new data set index  variable   inplace True    This gives a dataframe with index as column name of data and all data are present in  values  column

User · Answer

It s not smart enough to realize it s still a  vector  in math terms    Say rather that it s smart enough to recognize a difference in dimensionality   -   I think the simplest thing you can do is select that row positionally using iloc  which gives you a Series with the columns as the new index and the values as the values    gt  gt  gt  df   pd DataFrame  list range 5     columns   a    format i  for i in range 5     gt  gt  gt  df    a0  a1  a2  a3  a4 0   0   1   2   3   4  gt  gt  gt  df iloc 0  a0    0 a1    1 a2    2 a3    3 a4    4 Name  0  dtype  int64  gt  gt  gt  type     lt class  pandas core series Series  gt

User · Answer

You can transpose the single-row dataframe  which still results in a dataframe  and then squeeze the results into a series  the inverse of to frame    df   pd DataFrame  list range 5     columns   a    format i  for i in range 5      gt  gt  gt  df T squeeze      Or more simply  df squeeze   for a single row dataframe  a0    0 a1    1 a2    2 a3    3 a4    4 Name  0  dtype  int64   Note  To accommodate the point raised by  IanS  even though it is not in the OP s question   test for the dataframe s size   I am assuming that df is a dataframe  but the edge cases are an empty dataframe  a dataframe of shape  1  1   and a dataframe with more than one row in which case the use should implement their desired functionality   if df empty        Empty dataframe  so convert to empty Series      result   pd Series   elif df shape     1  1        DataFrame with one value  so convert to series with appropriate index      result   pd Series df iat 0  0   index df columns  elif len df     1        Convert to series per OP s question      result   df T squeeze   else        Dataframe with multiple rows   Implement desired behavior      pass   This can also be simplified along the lines of the answer provided by  themachinist   if len df   gt  1        Dataframe with multiple rows   Implement desired behavior      pass else      result   pd Series   if df empty else df iloc 0

User · Answer

You can also use stack   df  DataFrame  list range 5     columns       a      format I  for I in range 5     After u run df  then run  df stack    You obtain your dataframe in series

User · Answer

Another way - Suppose myResult is the dataFrame that contains your data in the form of 1 col and 23 rows   label your columns by passing a list of names myResult columns     firstCol      fetch the column in this way  which will return you a series myResult   myResult  firstCol    print type myResult    In similar fashion  you can get series from Dataframe with multiple columns

[python] Convert pandas data frame to series

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