For example, if I have a dataframe, df like this
col1 col2 col3
1 2 34
11 32 32
21 62 34
31 12 31
13 82 35
11 32 33
41 32 33
I want to loop 3 times and in each loop I want to take n rows one after another and in the last loop take rest of the rows. So it should take following rows in each loop
loop 1
1 2 34
11 32 32
loop 2
21 62 34
31 12 31
loop 3
13 82 35
11 32 33
41 32 33
Use numpy array_split
import numpy as np
num_chunks = 3
np.array_split(df,num_chunks) # this will split your array into num_chunks
You can assign new variables to each chunk as such
chunk1,chunk2,chunk3 = np.array_split(df,num_chunks)
You can use iterrows() method provided by dataframe and you can put some specific condition as per your requirement. For e.g. I could quickly come up with the following code, though it can be improved, but it prints the way you want to print it:
import pandas as pd
data = [[1, 2, 34],
[11, 32, 32],
[21, 62, 34],
[31, 12, 31],
[13, 82, 35],
[11, 32, 33],
[41, 32, 33]]
df = pd.DataFrame(data,columns=['col1','col2','col3'])
n = 2
count = 0
for index, row in df.iterrows():
if count == n or count == 2*n:
print("New line")
print(row['col1'], row['col2'], row['col3'])
count = count + 1
If you want to use loop, you can try following:
n = 2
loop_var = [(i+n) if (i+n+n)<len(df) else len(df) for i in range(0, len(df)-1, n)]
start = 0
for i in loop_var:
print(df[start:i])
start = i
Result:
col1 col2 col3
0 1 2 34
1 11 32 32
col1 col2 col3
2 21 62 34
3 31 12 31
col1 col2 col3
4 13 82 35
5 11 32 33
6 41 32 33
pandas. What code you tried to write for this, please let us know