Pandas: Using df.eval with string variables as conditional filtering-CodePudding

I have a simulated dataframe with one column created with:

df = pd.DataFrame({'A': np.arange(1,201)})

which is just a dataframe with numbers 1 to 200 with one column, "A". I would like to filter the dataframe based on a conditional statement like

df[df["A"] > 20]

but the column name, the boolean, >, and the value, 20, will have to be passed in as a string variable. So, I believe a dataframe.eval function in pandas should be used for this. I created a function called select_twenty for doing this. Here is it:

def select_twenty(input_df, column_name, boolean_arg, value):
    evaluated = input_df.eval(input_df[input_df[column_name]   boolean_arg   value])
    return evaluated

In the function above, input_df is the simulated dataframe above, column_name is the name of the chosen column and boolean_arg is the boolean, >, while value is the value 20. The last three arguments are passed in as strings in the function call:

select_twenty(df, "A", ">", "20")

When I call the function, it keeps giving me a UFuncTypeError. I have searched all over Google and do not know how to resolve it. I have not seen an example too where an eval in pandas was done this way. So, please, can someone help me with the filter? Thank you

CodePudding user response：

The error is relative to the inside of the eval argument, because you are trying to add the DataFrame column values with boolean_arg. What you are looking for is:

def select_twenty(input_df, column_name, boolean_arg, value):
    evaluated = input_df[input_df.eval(column_name   boolean_arg   value)]
    return evaluated

print(select_twenty(df, "A", ">", "20"))

       A
20    21
21    22
22    23
23    24
24    25
..   ...
195  196
196  197
197  198
198  199
199  200

[180 rows x 1 columns]