I have ten dataframes of event level data from ten different hockey seasons that each have a couple columns that I’d like to one hot encode with the intention of training a model on the historical data to make predictions about this years data . My current issue is that that columns that need to be encoded don’t contain all possible values in each dataframe. Just as an example there have been some expansion teams added, so dataframes for earlier years would not have these teams and thus they would not have an encoded column.

I have df1 with column ‘col’ & df2 with columns ‘code’ and ‘id’. Column ‘col’ in df1 is mapped to ‘code’ column in df2. When I am running the below code:

I would appreciate guidance removing the prefix ‘none_’ from the output of a styled pandas dataframe.
The prefix none_ is being used to identify the words, whose background color need to be changed to grey.
After the identified words’ background color has been changed to grey.
I would like to delete prefix none_ from the word.

Multiple data points are in a list. I want to combine them into one pandas DataFrame. Minimal example:

I’m merging two dataframes, one has 3 rows and the other has 100+ rows. What I am attempting to do is look at the IDs in DF1 and grab the corresponding ID data in DF2 and merge them together, ignoring the other rows. What seems to be happening it is just pulls in the first 3 rows form DF2 and isn’t matching on the IDs.

I have 2 different dataframes. I want to add the each column of the second dataframe to each column of the first dataframe.

i have a csv (semicolon separated, text qualifier “) which contains business partners with their data (address, bank account etc). This data, esp. the IBAN, needs to be validated. For the IBAN I use Schwifty:

I have a dataframe as below and I want to find streak ofh hot days.

Name Place Tyson New York Sophie Seattle I’ve tried various methods, but cant get the output as below: Name Place Tyson Place – New York Sophie Place – Seattle I need to add only Place column header to all the values of that column. python-3.x pandas dataframe New contributor Nick is a new contributor to […]

Given the following dataframe: