How do I change the header on a 2 column CSV file in python using the pandas library without creating a new file?

Question

I am working on a data analysis project. The file Data_Count.csv has two columns and was created using the pandas value_counts() function. One of the columns has a heading while the other does not. How can I make it so both columns have the headings "Distance" and "Frequency" respectively without having to create a new file? Here is my code so far. Sorry, I am new to python so my code isn't that efficient.

if __name__ == "__main__":
  count = int(input("How many distance entries do you wish to record?: "))
  with open('results.csv', 'w', newline='') as csvfile:
    writer = csv.writer(csvfile, delimiter=',')
    writer.writerows(calculate(count))

df = pd.read_csv("results.csv", header=None)
df.to_csv("results.csv", header=["Raw"], index=False)

df = pd.read_csv("results.csv")
ft = df["Raw"].value_counts(sort=False)
ft.to_csv('Data_Count.csv')

I want the final product to look like:

Distances       Frequency
1               1
2               3
3               2
4               1
5               2

It currently looks like:

             Raw
1            1
2            3
3            2
4            1
5            2

Furthermore, is it possible to somehow condense this code so that only one file is created instead of two (This is not important and doesn't have to be answered)? For reference, the calculate(count) function looks like:

def calculate(n):
    outputs = []
    for i in range(0, n):
        num1 = int(input("Enter first number: "))
        num2 = int(input("Enter second number: "))
        
        if NUMBERS.index(num1) < NUMBERS.index(num2):
            difference = subtract(num1, num2)
            
        elif NUMBERS.index(num1) > NUMBERS.index(num2):
            difference = distance(num1, num2)
            
        else:
            difference = 0
        outputs.append([difference])
    
    return outputs

jezrael · Accepted Answer · 2021-12-31 05:51:15Z

1

Use Series.rename_axis for set index name with DataFrame.reset_index, last add index=False to to_csv for avoid write default RangeIndex:

ft = (df["Raw"].value_counts(sort=False)
               .rename_axis('Distances')
               .reset_index(name='Frequency'))
ft.to_csv('Data_Count.csv', index=False)

edited Dec 31, 2021 at 5:51

answered Dec 30, 2021 at 9:42

jezrael

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1 Comment

Zach Young Over a year ago

Will that also produce the Frequency column name?

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