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trying to teach myself pandas.. and playing around with different dtypes
I have a df as follows
df = pd.DataFrame({'ID':[0,2,"bike","cake"], 'Course':['Test','Math','Store','History'] })
print(df)
ID Course
0 0 Test
1 2 Math
2 bike Store
3 cake History
the dtype of ID is of course an object. What I want to do is remove any rows in the DF if the ID has a string in it.
I thought this would be as simple as..
df.ID.filter(regex='[\w]*')
but this returns everything, is there a sure fire method for dealing with such things?
489
Use pandas. DataFrame. drop() method to delete/remove rows with condition(s).
Pandas provide data analysts a way to delete and filter data frame using dataframe. drop() method. We can use this method to drop such rows that do not satisfy the given conditions.
First of all, create a data frame. Then, use single square subsetting with apply function to remove rows that contains a specific number.
DataFrame. drop() method you can drop/remove/delete rows from DataFrame. axis param is used to specify what axis you would like to remove. By default axis = 0 meaning to remove rows.
You can using to_numeric
df[pd.to_numeric(df.ID,errors='coerce').notnull()]
Out[450]:
Course ID
0 Test 0
1 Math 2
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