numpy - Loop over lists and concat in pd.dataframe -


i'm trying mulitply dataframe numpy array follows:

import numpy np pandas import* import pandas pd  c = np.arange(30).reshape(5, 6)  df = pd.dataframe(np.arange(48).reshape((8, 6)), columns=list('abcdef')) pxc = df / df.shift(1) - 1  def concatarrays(a, b):      carrays_0 = np.sum(a[0,]*b, axis=1)      carrays_1 = np.sum(a[1,]*b, axis=1)      carrays_2 = np.sum(a[2,]*b, axis=1)      carrays_3 = np.sum(a[3,]*b, axis=1)      carrays_4 = np.sum(a[4,]*b, axis=1)      #(...)       pieces = [carrays_0, carrays_1, carrays_2, carrays_3, carrays_4] #(...)      concatenated = concat(pieces, axis=1, join='outer')      return concatenated  print concatarrays(c, pxc)

i create loop 'concatenated automatic regardless of number of lists in c, avoiding writing each carray_i hand.

thanx

strongly suspect that

def concatarrays(a, b):       pieces = [a*b in a] #(...)      concatenated = concat(pieces, axis=1, join='outer')      return concatenated

will trick, depend on if pandas behaves expect in terms of iterating on data frames.


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