CODEWITHSUNDEEP
pythonpandasappend
Adithya Kumar
Adithya Kumar

Reputation: 159

Python append to dataframe column based on condition

I want to count the number of pipe symbol occurrence in a column of a data frame and it equals 5, then I need to append another pipe(|) symbol to the existing value. 

df2['smartexpenseid']

0      878497|253919815?HOTEL?141791520780|||305117||
1                                   362593||||35068||
2         |231931871509?CARRT?231940968972||||177849|
3       955304|248973233?HOTEL?154687992630||||93191|
4                                 27984||||5883|3242|
5    3579321|253872763?HOTEL?128891721799|92832814|||
6            127299|248541768?HOTEL?270593355555|||||
7         |231931871509?CARRT?231940968972||||177849|
8                                   831665||||80658||
9              |247132692?HOTEL?141790728905||||6249|

For ex: for row number 5, the (|) count is 5, so it should add another (|) to the existing value and for other rows, since count is 6, we just leave it as it is. Can somebody help me with this ?

I tried these 

if df2['smartexpenseid'].str.count('\|')==5:
    df2['smartexpenseid'].append('\|')

This is throwing me error saying "The truth value of a Series is ambiguous"

and also 

a = df2['smartexpenseid'].str.count('\|')
if 5 in a:
    a.index(5)

Upvotes: 1

Views: 1537

Answers (1)

Alex
Alex

Reputation: 19104

So you have the vectorized str methods down. Now you need to conditionally append an extra '|' character. See Pandas section on masking for more info.

m = df2['smartexpenseid'].str.count('\|') == 5
df2.loc[m, 'smartexpenseid'] = df2['smartexpenseid'][m].values + '|'

Upvotes: 3

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