import pandas as pd
# Load the CSV file into a Pandas DataFrame
df = pd.read_csv('payout-export.csv')

print(df)

    Payout Date Status  Charges  Refunds  Adjustments  Reserved Funds   Fees  \
0    2023-06-06   paid   133.17     0.00          0.0             0.0   6.77   
1    2023-06-02   paid    52.98     0.00          0.0             0.0   1.84   
2    2023-05-31   paid   114.53     0.00          0.0             0.0   5.77   
3    2023-05-30   paid    53.96    -7.99          0.0             0.0   2.46   
4    2023-05-23   paid  1050.77     0.00          0.0             0.0  42.07   
..          ...    ...      ...      ...          ...             ...    ...   
111  2022-07-21   paid    36.98     0.00          0.0             0.0   1.37   
112  2022-07-20   paid   157.85     0.00          0.0             0.0   7.27   
113  2022-07-19   paid   527.81     0.00          0.0             0.0  20.44   
114  2022-07-18   paid   110.94     0.00          0.0             0.0   4.11   
115  2022-07-15   paid   369.80     0.00          0.0             0.0  13.70   

     Retried Amount    Total Currency  
0               0.0   126.40      USD  
1               0.0    51.14      USD  
2               0.0   108.76      USD  
3               0.0    43.51      USD  
4               0.0  1008.70      USD  
..              ...      ...      ...  
111             0.0    35.61      USD  
112             0.0   150.58      USD  
113             0.0   507.37      USD  
114             0.0   106.83      USD  
115             0.0   356.10      USD  

[116 rows x 10 columns]

import pandas as pd

# Read the CSV file into a pandas DataFrame
df = pd.read_csv('payout-export.csv')

# Select the 'Charges' column
charges_column = df['Charges']

# Print the 'Charges' column
print(charges_column)

0       133.17
1        52.98
2       114.53
3        53.96
4      1050.77
        ...   
111      36.98
112     157.85
113     527.81
114     110.94
115     369.80
Name: Charges, Length: 116, dtype: float64

import pandas as pd

# Read the CSV file into a pandas DataFrame
df = pd.read_csv('payout-export.csv')

# Calculate the total of the 'Charges' column
total_charges = df['Charges'].sum()

# Print the total charges
print('Total Charges:', total_charges)

Total Charges: 24787.109999999997

import pandas as pd

# Read the CSV file into a pandas DataFrame
df = pd.read_csv('payout-export.csv')

# Select the 'Fees' column
fees_column = df['Fees']

# Print the 'Fees' column
print(fees_column)

0       6.77
1       1.84
2       5.77
3       2.46
4      42.07
       ...  
111     1.37
112     7.27
113    20.44
114     4.11
115    13.70
Name: Fees, Length: 116, dtype: float64

import pandas as pd

# Read the CSV file into a pandas DataFrame
df = pd.read_csv('payout-export.csv')

# Calculate the total of the 'Fees' column
total_fees = df['Fees'].sum()

# Print the total Fees
print('Total Fees:', total_fees)

Total Fees: 1040.2700000000002

import pandas as pd

# Read the CSV file into a pandas DataFrame
df = pd.read_csv('payout-export.csv')

total_charges = df['Charges'].sum()

total_fees = df['Fees'].sum()

print('Total Amount:', '$', total_charges - total_fees)

Total Amount: $ 23746.839999999997