How to manipulate values of a dataframe without depending on the column name

Question

I have a dataframe which has columns like below:

MultiIndex([('Longitude', 'Field1'),
            ('Latitude', 'Field1'),
            ('Name with Name Text', 'Field1'),
            ('Name with Name Text', 'Field2'),
            ('IsPresent', 'Field1')],)

A csv example of this would be

I want to iterate through each row in the data and for each value of field I want to replace certain characters, if they exist. For example, replace 'X' with 'Y'. But I don't want to depend on the column name as it can change. I want to iterate over each value and strip the character. Below iteration has field names so can't use it.

for i, j in df1.iterrows():
    print(j['Name with Name Text']['Field1'])

score 0 · Answer 1 · answered Aug 18 '20 at 11:44

0

Although you can of course iterate row by row as described in the comment above, you can also try to find a function that does what you want on the entire column "at once".

For example, replace all "Y" to "Z" in column "col1"

    df["col1"] = df["col1"].apply(lambda x: x.replace("Y", "Z"))

answered Aug 18 '20 at 11:44

Dustin

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Is it possible without the column name? – user1298426 Aug 18 '20 at 12:21
Could you be more specific? Do you want to reference the column by index, or would you like to perform the operation on the entire dataframe? – Dustin Aug 18 '20 at 12:23
entire dataframe as column names can change so don't want to be dependent on column names. – user1298426 Aug 18 '20 at 12:25
Try this for column index 2: `df.loc[:,2]' – Dustin Aug 18 '20 at 12:35

How to manipulate values of a dataframe without depending on the column name

1 Answers1