Iterating Through Data Frame Rows

[JoeDainton123]

Hello all

I have a dataframe which i have imported from excel.

It has column headings and below the column headings it has all of my data in rows.

I want to LOOP through each row of the first column and if it is equal to a value say 123 then i just want to remove it.

I want to LOOP through each item in the data frame.

so far i have:-

t = 0 while t < len(Report): Value = Report.iloc[t,0] #the value i want to check is always in the 0 column index if Value == Report.iloc[t,0]: #how do i delete the the row???? t=t+1

deleting the rows is proving to be very difficult.

Can anyone help provide some guidance.

Thank you.

[scidam]

Usually, you don't need to use pure Python loops to drop rows;

df[~(df.iloc[:,0] == value)] # remove row if a specific value in the first column;

or you can use .drop method

df.drop(df[df.iloc[:,0] == value].index, inplace=True)

[Pedroski55]

Not being a scientist, I don't have any large amounts of experimental data to process, but pandas is interesting!

Have a look here perhaps!

import pandas as pd # open the file xl_file = '/home/pedro/myPython/pandas/delete_row.xlsx' df = pd.read_excel(xl_file) """ >>> df col1 col2 col3 col4 col5 col6 0 123 1 2 3 4 5 1 123 2 3 4 5 6 2 456 3 4 5 6 7 3 456 4 5 6 7 8 4 789 5 6 7 8 9 5 789 6 7 8 9 10 6 123 7 8 9 10 11 """ # Drop a row by condition df2 = df[df.col1 != 123] """ >>> df2 col1 col2 col3 col4 col5 col6 2 456 3 4 5 6 7 3 456 4 5 6 7 8 4 789 5 6 7 8 9 5 789 6 7 8 9 10 >>> """