Swapping dataframe column data without changing the index for the table

Question

While compiling a pandas table to plot certain activity on a tool I have encountered a rare error in the data that creates an extra 2 columns for certain entries. This means that one of my computed column data goes into the table 2 cells further on that the other and kills the plot.

I was hoping to find a way to pull the contents of a single cell in a row and swap it into the other cell beside it, which contains irrelevant information in the error case, but which is used for the plot of all the other pd data.

I've tried a couple of different ways to swap the data around but keep hitting errors.

My attempts to fix it include:

for rows in df['server']:
    if '%USERID' in line:
        df['server'] = df[7] # both versions of this and below
        df['server'].replace(df['server'],df[7])
    else:
        pass

if '%USERID' in df['server']: # Attempt to fix missing server name
    df['server'] = df[7];
else:
    pass

if '%USERID' in df['server']:
    return row['7'], row['server']
else:
    pass

I'd like the data from column '7' to be replicated in 'server', only in the case of the error - where the data in the cell contains a string starting with '%USERID'

Welcome to SO, please provide a minimal reproducible example — Yuca
– Yuca, Commented Jul 3, 2019 at 12:53

Saltire78 · Accepted Answer · 2019-07-15 09:14:59Z

1

Turns out I was over-thinking this one. I took a step back, worked the code a bit and solved it.

Rather than trying to smash a one-size fits all bit of code for the all data I built separate lists for the general data and 2 exception I found, by writing a nested loop and created 3 data frames. These were easy enough to then manipulate individually, and finally concatenate together. All working fine now.

answered Jul 15, 2019 at 9:14

Saltire78

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