*Input:*
df["waiting_time"].value_counts()
*Output:*
2 days 6724
4 days 5290
1 days 5213
7 days 4906
6 days 4037
...
132 days 1
125 days 1
117 days 1
146 days 1
123 days 1
Name: waiting_time, Length: 128, dtype: int64
I tried:
df['wait_dur'] = df['waiting_time'].values.astype(str)
and I've tried apply as well. No changes to the data type, it stays the same.
CodePudding user response:
You need to skip the 'values' part in your code:
df['wait_dur'] = df['waiting_time'].astype(str)
If you check first row for example, you will get:
type(df['wait_dur'][0])
<class 'str'>
CodePudding user response:
df = df.applymap(str)
This should work, it applies the map
string
throughout.
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