How to check if a column of DataFrame contain float type?

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For example, I've got this data frame.

 import pandas as pd
 import numpy as np
 data = {'state': ['Ohio', 'Florida', 'Texas', 'Washington', 'Arizona', 'Nevada'],
         'year' : [2000, 2000, 2000, 2000, 2000, 2000],
         'event': [1.5, "None", 3.6, 2.4, "None", 3.2]}

frame = pd.DataFrame(data)
frame

OUT>>

    state       year    event
0   Ohio        2000    1.5
1   Florida     2000    None
2   Texas       2000    3.6
3   Washington  2000    2.4
4   Arizona     2000    None
5   Nevada      2000    3.2

Question/ How to filter the event column by display the DataFrame with only the float type based on the event column?

Looking the result to be like

   state        year    event
0   Ohio        2000    1.5
1   Texas       2000    3.6
2   Washington  2000    2.4
3   Nevada      2000    3.2
pandas dataframe python types
2 Answers

You can create a subset of the dataframe by checking which values are float in the 'event' column. The reset index is to renumber the index rows.

frame[frame['event'].apply(lambda x: isinstance(x,float))].reset_index(drop=True)
user_154480220

Try:

frame[pd.to_numeric(frame.event, errors='coerce').notnull()]

Or even:

frame.query("event != 'None'")

Outputs:

        state  year event
0        Ohio  2000   1.5
2       Texas  2000   3.6
3  Washington  2000   2.4
5      Nevada  2000   3.2
user_91922840
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