Pandas Series Conditionally Change String

Question

I am trying to change the strings in a Pandas Series by a condition. If the string name is say 'A', it should be 'AA'. The code snippet below works but it is very un elegant and inefficient. I am passing a Pandas series as an argument as I said. Is there any other way to accomplish this?


def conditions(x):
    if x == 'A':
        return "AA"
    elif x == 'B':
        return "BB"
    elif x == 'C':
        return "CC"
    elif x == 'D':
        return "DD"
    elif x == 'E':
        return "EE"
    elif x == 'F':
        return "FF"
    elif x == 'G':
        return "GG"
    elif x == 'H':
        return "HH"
    elif x == 'I':
        return "I"
    elif x == 'J':
        return "JJ"
    elif x == 'K':
        return "KK"
    elif x == 'L':
        return 'LL'

func = np.vectorize(conditions)
test = func(rfqs["client"])

Hammurabi · Accepted Answer · 2021-07-19 23:42:57Z

2

If you are just trying to repeat a given string, you can add the string to itself across all rows at once. If you have some other condition, you can specify that condition and add the string to itself only for rows that meet the criteria. See this toy example:

df = pd.DataFrame({'client': ['A', 'B', 'Z']})

df.loc[df['client'].str.contains('[A-L]'), 'client'] = df['client'] * 2

to get

  client
0     AA
1     BB
2      Z

answered Jul 19, 2021 at 23:42

Hammurabi

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Comments

IoaTzimas · Accepted Answer · 2021-07-19 23:42:51Z

1

You can use a dictionary to avoid all those if elses:

d = {i:2*i for i in ('A', 'B', 'C', 'D', 'E', 'F', 'G', 'H', 'I', 'J', 'K', 'L')} 

test = rfqs["client"].apply(lambda x: d[x] if x in d else x)

answered Jul 19, 2021 at 23:42

IoaTzimas

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Comments

rhug123 · Accepted Answer · 2021-07-19 23:59:38Z

1

Here is another way:

l = list('ABCDEFGHIJKL')
df['col'] = df['col'].mask(df['col'].isin(l),df['col'].str.repeat(2))

With np.where()

df['col'].mul(np.where(df['col'].isin(l),2,1))

With map()

df['A'].mul(df['A'].map({i:2 for i in l}).fillna(1).astype(int))

edited Jul 19, 2021 at 23:59

answered Jul 19, 2021 at 23:51

rhug123

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