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remove [] from output values in a dataframe

Time:12-16

I'm pulling data from google trends and the output values come out as follows:

                 date value
0 2017-01-01 03:00:00  [65]
1 2017-01-01 03:01:00  [66]
2 2017-01-01 03:02:00  [77]
3 2017-01-01 03:03:00  [64]
4 2017-01-01 03:04:00  [94]

I've trimmed what I don't need. My issue is I need to remove the brackets and make the calue column an int. I've tried the following:

result['value'].apply(lambda x: pd.Series(str(x).replace('[', '').replace(']', '')))

But I get the same output either way. Any thoughts or suggestions?

CodePudding user response:

You can also do:

df['value'] = df['value'].explode()

Output:

                  date value
0 2017-01-01  03:00:00    65
1 2017-01-01  03:01:00    66
2 2017-01-01  03:02:00    77
3 2017-01-01  03:03:00    64
4 2017-01-01  03:04:00    94

CodePudding user response:

You can do

df['value'] = df['value'].str[0]
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