Replacement of values in such cases could be done using the lambda() function and x.replace, as demonstrated in the code below it also works for all the values in data frame if you need to change it in many rows
df = pd.DataFrame(data, index = ['Cochice','Pima','Santa Cruz','Maricopa','Yuma']) df Create a capitalization lambda function capitalizer =lambdax: x.upper() Apply the capitalizer function over the column ‘name’ apply() can apply a function along any axis of the dataframe df['nam...
It's possible to enclose both functions within a function in the context oflambda. df[df.name.apply(lambda x: is_long(x) and is_short(x))] to get name age 0 foo 10 2 baz 14 Pandas dataframe apply refer to previous row to, I have the following pandas dataframe containing 2 columns...
Python - How to change the datetime format in Pandas, My dataframe has a DOB column (example format 1/1/2016) which by default gets converted to Pandas dtype 'object'. Converting this to date format with df ['DOB'] = pd.to_datetime (df ['DOB']), the date gets converted to: 2016...
Conversion of Boolean values to integers in a pandas DataFrame during the application of a multiplication function [duplicate], Pandas substitution of boolean value with string or integer, Transforming a single integer into multiple boolean columns using