The image below is my list where I want to edit two columns for future analysis during the data cleaning process:
When running the code bike_share_data["start_lng"].dtypes
, the contents of the "start_lng" and "end_lng" columns are dtype('o')
Now I want to replace the underscore (_) with a minus sign (-) and make the data type of the entire column a float.
I have tested the code in isolation as shown below:
import pandas as pd d =[ '_1.0', '_2.0', '_3.0'] d=[s.replace('_','-') for s in d] print(d)
The result is ['-1.0', '-2.0', '-3.0'].
But it cannot be achieved on the bike_share_data["start_lng"] column. what should I do?
You can use the str.replace()
method to perform the replacement and then use the astype()
to change type of data.
# sample DataFrame with a "start_lng" column containing strings data = {'start_lng': ['_1.0', '_2.0', '_3.0']} Bike_share_data = pd.DataFrame(data) # Replace underscores with minus signs & convert the column to float Bike_share_data["start_lng"] = Bike_share_data["start_lng"].str.replace('_', '-').astype(float)
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