Delete specific row and corresponding file in python
I want to delete 90% of rows which have "steering" value qual to 0. And there is a corresponding image file for all three f them, center, left and right. I want to delete them too. The csv file is like this:
I have written the following code to at least get the files which have steering value 0. All I need is the code to randomly get 90% of those files and delete them.
with open('data/driving_log.csv') as csvfile:
reader = csv.reader(csvfile)
for i,line in enumerate(reader):
lines.append(line)
index.append(i)
lines = np.delete(lines,(0), axis = 0)
for i, line in enumerate(lines):
#print(type(line[3].astype(np.float)))
line_no.append(line[3].astype(np.float32))
#print(line_no[i])
if line_no[i]==0.0:
# this gets the first column of the row.
for j in range(3):
source_path = line[j]
filename = source_path.split('/')[-1]
print(filename)
count += 1
I think this will do what you want:
import csv
from random import randint
from os import remove
# Create a 2D list from which we can work with
lines = []
with open('data/driving_log.csv', newline='') as csvfile:
reader = csv.reader(csvfile)
for line in reader:
lines.append(line)
# Find 10% of total lines (to keep), not including header row
numToKeep = round(sum(1 for i in lines if i[3] == '0') * 0.1)
# Save 10% of lines to a new 2D list
toKeep = []
for i in range(numToKeep):
while True:
index = randint(1, len(lines)-1)
# Make sure we haven't already selected the same line
if lines[index] not in toKeep and lines[index][3] == '0':
toKeep.append(lines[index])
break
# Deleting all files of the selected 90% of rows
for i, line in enumerate(lines):
if i == 0: # Omit the header row
continue
if lines[i][3] != '0': # Keep rows that don't have a steering value of 0
toKeep.append(lines[i])
if line not in toKeep:
print("Deleting: {}".format(line))
for i in range(3):
remove(line[i])
with open('data/driving_log.csv', 'w', newline='') as csvfile:
writer = csv.writer(csvfile)
writer.writerows([lines[0]]) # Put the header back in
writer.writerows(toKeep)
I realize this isn't the most elegant solution. I'm not familiar with numpy and don't have time to learn it right now, but this should work.
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