How To Remove A Substring Of String In A Dataframe Column?

I have this simplified dataframe: ID, Date 1 8/24/1995 2 8/1/1899 :00 How can I use the power of pandas to recognize any date in the dataframe which has extra :00 and removes it.

Solution 1:

You need to assign the trimmed column back to the original column instead of doing subsetting, and also the str.replace method doesn't seem to have the to_replace and value parameter. It has pat and repl parameter instead:

df["Date"] = df["Date"].str.replace("\s:00", "")

df#   ID       Date#0   1  8/24/1995#1   2   8/1/1899

Solution 2:

To apply this to an entire dataframe, I'd stack then unstack

df.stack().str.replace(r'\s:00', '').unstack()

functionalized

def dfreplace(df, *args, **kwargs):
    s = pd.Series(df.values.flatten())
    s = s.str.replace(*args, **kwargs)
    return pd.DataFrame(s.values.reshape(df.shape), df.index, df.columns)

Examples

df = pd.DataFrame(['8/24/1995', '8/1/1899 :00'], pd.Index([1, 2], name='ID'), ['Date'])

dfreplace(df, '\s:00', '')

---

rng = range(5)
df2 = pd.concat([pd.concat([df for _ in rng]) for _ in rng], axis=1)

df2

dfreplace(df2, '\s:00', '')