Converting a csv file containing pixel values to it's equivalent images - python-3.x

Question

This is my first time working with such a dataset.
I have a .csv file containing pixel values (48x48 = 2304 columns) of images, with their labels in the first column and the pixels in the subsequent ones, as below:
A glimpse of the dataset
I want to convert these pixels into their images, and store them into different directories corresponding to their respective labels. Now I have tried the solution posted here but it doesn't seem to work for me.
Here's what I've tried to do:
labels = ['Fear', 'Happy', 'Sad']
with open('dataset.csv') as csv_file:
csv_reader = csv.reader(csv_file)
fear = 0
happy = 0
sad = 0
# skip headers
next(csv_reader)
for row in csv_reader:
pixels = row[1:] # without label
pixels = np.array(pixels, dtype='uint8')
pixels = pixels.reshape((48, 48))
image = Image.fromarray(pixels)
if csv_file['emotion'][row] == 'Fear':
image.save('C:\\Users\\name\\data\\fear\\im'+str(fear)+'.jpg')
fear += 1
elif csv_file['emotion'][row] == 'Happy':
image.save('C:\\Users\\name\\data\\happy\\im'+str(happy)+'.jpg')
happy += 1
elif csv_file['emotion'][row] == 'Sad':
image.save('C:\\Users\\name\\data\\sad\\im'+str(sad)+'.jpg')
sad += 1
However, upon running the above block of code, the following is the error message I get:
Traceback (most recent call last):
File "<ipython-input-11-aa928099f061>", line 18, in <module>
if csv_file['emotion'][row] == 'Fear':
TypeError: '_io.TextIOWrapper' object is not subscriptable
I referred to a bunch of posts that solved the above error (like this one), but I found that the people were trying their hand at a relatively different problem than mine, and others I couldn't understand.
This may well be a very trivial question, but as I mentioned earlier, this is my first time working with such a dataset. Kindly tell me what am I doing wrong and how I can fix my code.

Answer 1

Try -
if str(row[0]) == 'Fear':
And in a similar way for the other conditions:
elif str(row[0]) == 'Happy':
elif str(row[0]) == 'Sad':
(a good practice is to just save the first value of the array as a variable)

Answer 2

The first problem that arose was that the first row was just the column names. In order to take care of this, I used the skiprows parameter like so:
raw = pd.read_csv('dataset.csv', skiprows = 1)
Secondly, I moved the labels column to the end due to it being in the first column. For my own convenience.
Thirdly, after all the preparations were done, the dataset won't iterate over the whole row, and instead just took in the value of the first row and first column, which gave an issue in resizing. So I instead used the df.itertuples() like so:
for row in data.itertuples(index = False, name = 'Pandas'):
Lastly, thanks to #HadarM 's suggestions, I was able to get it to work.
Modified code of the above code snippet that was the problematic block:
for row in data.itertuples(index = False, name = 'Pandas'):
pixels = row[:-1] # without label
pixels = np.array(pixels, dtype='uint8')
pixels = pixels.reshape((48, 48))
image = Image.fromarray(pixels)
if str(row[-1]) == 'Fear':
image.save('C:\\Users\\name\\data\\fear\\im'+str(fear)+'.jpg')
fear += 1
elif str(row[-1]) == 'Happy':
image.save('C:\\Users\\name\\data\\happy\\im'+str(happy)+'.jpg')
happy += 1
elif str(row[-1]) == 'Sad':
image.save('C:\\Users\\name\\data\\sad\\im'+str(sad)+'.jpg')
sad += 1
print('done')