每隔 n 行切片 Pandas DataFrame

Question

I have a CSV file, which I read in as a pandas DataFrame. I want to slice the data after every nth row and store the it as an individual CSV.

My data looks somewhat like this:

index,acce_x,acce_y,acce_z,grav_x,grav_y,grav_z
0,-2.53406373,6.92596131,4.499464420000001,-2.8623820449999995,7.850541115,5.129520459999999
1,-2.3442032099999994,6.878311170000001,5.546690349999999,-2.6456542850000004,7.58022081,5.62603916
2,-1.8804458600000005,6.775125179999999,6.566146829999999,-2.336306185,7.321197125,6.088656729999999
3,-1.7059021099999998,6.650866649999999,7.07060242,-2.1012737650000006,7.1111130000000005,6.416324900000001
4,-1.6802886999999995,6.699703990000001,7.15823367,-1.938001715,6.976289879999999,6.613534820000001
5,-1.6156433,6.871610960000001,7.13333286,-1.81060772,6.901037819999999,6.72789553
6,-1.67286072,7.005918899999999,7.22047422,-1.722352455,6.848503825,6.8044359100000005
7,-1.56608278,7.136883599999999,7.150566069999999,-1.647941205,6.821055315,6.850329440000001
8,-1.3831649899999998,7.2735946999999985,6.88074028,-1.578703155,6.821634375,6.866061665000001
9,-1.25986478,7.379898050000001,6.590330490000001,-1.5190086099999998,6.839881785,6.861375744999999
10,-1.1101097050000002,7.48500525,6.287461959999999,-1.4641099750000002,6.870566649999999,6.842625039999999

For example, I would like to slice it after every 5th row and store the rows indexed 1-4 and 5-9 each in a single CSV (so in this case I would get 2 new CSVs), row 10 should be discarded. One issue is that I'll have to apply this to multiple files which differ in length as well as naming the newly created CSVs.

Answer 1

You can do it with a for loop:

for i in range(round(len(df)/5)): #This ensures all rows are captured
   df.loc[i*5:(i+1)*5,:].to_csv('Stored_files_'+str(i)+'.csv')

So the first iteration it'll be rows 0 to 5 stored with name "Stored_files_0.csv The second iteration rows 5 to 10 with name "Stored_files_1.csv" And so on...