Pandas Creating DataFrame from Series

Question

My current code is shown below - I m importing a MAT file and trying to create a DataFrame from variables within it   mat   loadmat file path     load mat-file Variables   mat keys        identify variable names  df   pd DataFrame           Initialise DataFrame  for name in Variables       B   mat name      s   pd Series  B   1     So within the loop I can create a series of each variable  they re arrays with two columns - so the values I need are in column 2   My question is how do I append the series to the dataframe  I ve looked through the documentation and none of the examples seem to fit what I m trying to do   Best Regards   Ben

User · Answer

No need to initialize an empty DataFrame (you weren't even doing that, you'd need pd.DataFrame() with the parens).

Instead, to create a DataFrame where each series is a column,

make a list of Series, series, and
concatenate them horizontally with df = pd.concat(series, axis=1)

Something like:

series = [pd.Series(mat[name][:, 1]) for name in Variables]
df = pd.concat(series, axis=1)

User · Answer

I guess anther way  possibly faster  to achieve this is  1  Use dict comprehension to get desired dict  i e   taking 2nd col of each array  2  Then use pd DataFrame to create an instance directly from the dict without loop over each col and concat   Assuming your mat looks like this  you can ignore this since your mat is loaded from file    In  135   mat     a   np random randint 5  size  4 2               b   np random randint 5  size  4 2     In  136   mat Out 136      a   array   2  0            3  4            0  1            4  2      b   array   1  0            1  1            1  0            2  1       Then you can do   In  137   df   pd DataFrame   name mat name    1  for name in mat    In  138   df Out 138       a  b 0  0  0 1  4  1 2  1  0 3  2  1   4 rows x 2 columns

User · Answer

Here is how to create a DataFrame where each series is a row   For a single Series  resulting in a single-row DataFrame    series   pd Series  1 2   index   a   b    df   pd DataFrame  series     For multiple series with identical indices   cols     a   b   list of series    pd Series  1 2  index cols   pd Series  3 4  index cols   df   pd DataFrame list of series  columns cols    For multiple series with possibly different indices   list of series    pd Series  1 2  index   a   b     pd Series  3 4  index   a   c     df   pd concat list of series  axis 1  transpose     To create a DataFrame where each series is a column  see the answers by others  Alternatively  one can create a  DataFrame where each series is a row  as above  and then use df transpose    However  the latter approach is inefficient if the columns have different data types

[python] Pandas: Creating DataFrame from Series

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