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I have a pandas dataframe df with the contents below:
Date Factor Expiry Grade
0 12/31/1991 2.138766 3/30/1992 -3.33%
1 10/29/1992 2.031381 2/8/1993 -1.06%
2 5/20/1993 2.075670 6/4/1993 -6.38%
I would like the remove the % character from all the rows in the Grade column. The result should look like this:
Date Factor Expiry Grade
0 12/31/1991 2.138766 3/30/1992 -3.33
1 10/29/1992 2.031381 2/8/1993 -1.06
2 5/20/1993 2.075670 6/4/1993 -6.38
I am using Python v3.6.
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Use drop() method to delete rows based on column value in pandas DataFrame, as part of the data cleansing, you would be required to drop rows from the DataFrame when a column value matches with a static value or on another column value.
To remove a specific word in a string variable in Python, the easiest way is to use the Python built-in string replace() function. string_with_words = "This is a string." string_without_is = string_with_words. replace("is","") print(string_without_is) #Output: This a string.
The str. strip() function is used to remove leading and trailing characters. Strip whitespaces (including newlines) or a set of specified characters from each string in the Series/Index from left and right sides. Equivalent to str.
Using str.replace would work:
df['Grade'] = df['Grade'].str.replace('%', '')
You can use string slicing and then convert to a numeric type via pd.to_numeric:
df['Grade'] = pd.to_numeric(df['Grade'].astype(str).str[:-1], errors='coerce')
Conversion to float is recommended as a series of strings will be held in a generic and inefficient object dtype, while numeric types permit vectorised operations.
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