如何在每个循环后保存 output in.csv 而不覆盖 Pandas？

Question

I want to save my output in.csv. When I am running my while loop and saving the output, My output is only saving for the last iteration. Its not saving my all iteration value.

Also, I want to skip the zero value rows while printing my output.

This is my code:

import pandas as pd `#pandas library
sample = pd.DataFrame(pd.read_csv ("Sample.csv")) #importing .csv as pandas DataFrame

i = 0
while (i <= 23):
    print('Value for', i) `#i vale`
    sample2 = (sample[sample['Hour'] == i])`#Data for every hour`
    sample3 = (sample2[(sample2['GHI']) == (sample2['GHI'].max(0))]) `#Max value from sample3 DataFrame`
    sample3 = sample3.loc[sample3.ne(0).all(axis=1)]`ignoring all rows having zero values`
    print(sample3)  `print sample3`
    sample3.to_csv('Output.csv')`trying to save for output after every iteration`
    i = i + 1

Answer 1

An other way of doing what you want to do is to get rid of your loop, like this:

sample_with_max_ghi = sample.assign(max_ghi=sample.groupby('Hour')['GHI'].transform('max'))
sample_filtered = sample_with_max_ghi[sample_with_max_ghi['GHI'] == sample_with_max_ghi['max_ghi']]
output_sample = sample_filtered.loc[sample_filtered.ne(0).all(axis=1)].drop('max_ghi', axis=1)
output_sample.to_csv('Output.csv')

Some explanations:

1.

sample_with_max_ghi = sample.assign(max_ghi=sample.groupby('Hour')['GHI'].transform('max'))

This line add a new column to your dataframe containing the max of GHI column for your group of Hour

2.

sample_filtered = sample_with_max_ghi[sample_with_max_ghi['GHI'] == sample_with_max_ghi['max_ghi']]

This line filters only rows where the GHI value is actually the max of its Hour group

3.

output_sample = sample_filtered.loc[sample_filtered.ne(0).all(axis=1)].drop('max_ghi', axis=1)

And apply the last filter to get rid of the 0 values rows

Answer 2

while the loop is running adding the value at every loop to rename the csv file will make it to look unique and solve your problem.. eg:

import pandas as pd `#pandas library
sample = pd.DataFrame(pd.read_csv ("Sample.csv")) #importing .csv as pandas DataFrame

i = 0
while (i <= 23):
    print('Value for', i) `#i vale`
    sample2 = (sample[sample['Hour'] == i])`#Data for every hour`
    sample3 = (sample2[(sample2['GHI']) == (sample2['GHI'].max(0))]) `#Max value from sample3 DataFrame`
    sample3 = sample3.loc[sample3.ne(0).all(axis=1)]`ignoring all rows having zero values`
    print(sample3)  `print sample3`
    sample3.to_csv(str(i)+'Output.csv')`trying to save for output after every iteration`
    i = i + 1