How to reshape every nth row's data using pandas?

Question

I need help in reshaping a data in csv file that have over 10000 row by 10 each. For example I have this csv file :

Ale Brick
1   ww
2   ee
3   qq
3   xx
5   dd
         


        

Answer 1

You can group by every 10th row and then reshape the values

df.groupby(np.repeat(np.arange(len(df) / 10), 10))['Brick'].apply(lambda x: x.values.reshape(2,5))

0.0    [[ww, ee, qq, xx, dd], [gg, hh, tt, yy, uu]]
1.0    [[ii, oo, pp, mm, ww], [zz, cc, rr, tt, ll]]

Answer 2

import pandas as pd

df = pd.read_csv(`"`test.csv`"`)

data = df['Brick']

k=int(len(data)/10)+1

for x in range(k):

    temp=data[10*x:10*(x+1)]

    print temp.values.reshape(2,5)

Answer 3

You need to make use of the modulo operator to "batch" reshape your column. You're on the right track. You just need another iterator to do the modulo operation.

import pandas as pd

df = pd.DataFrame({'brick': ['xx','yy','xa','bd','ev','bb','oo','pp','qq','bn','nv','bn','rr','qw','bn','cd','fd','bv','nm','ty']})

start = 0  # set start to 0 for slicing
for i in range(len(df.index)):
    if (i + 1) % 10 == 0:  # the modulo operation
        result = df['brick'].iloc[start:i+1].reshape(2,5)
        print result
        start = i + 1  # set start to next index

Output:

[['xx' 'yy' 'xa' 'bd' 'ev']
 ['bb' 'oo' 'pp' 'qq' 'bn']]
[['nv' 'bn' 'rr' 'qw' 'bn']
 ['cd' 'fd' 'bv' 'nm' 'ty']]