I am trying to solve this problem with my code – I have developed a function in order to figure out the sum total of a value for a particular year using pandas dataframes.

With that code below, i can generate a dataframe with all business days between two dates, but i dont know how to filter to only be included in dataframe the first business day of each month.

I have a dataframe, df, such that when I print it out, it looks like:

So yesterday i was having issues trying to define all column via data frame’s to_sql method. For the most part this works just fine.

I try to filter a dataframe using the following expression: I am seeking the times “col” changes to “val”:

I have the following data-frame (read from a csv file):

I have the following data-frame (read from a csv file):

I am trying to automate sth but struggling with it. It is actually my first code in Python and what I would like to order this data frame by Hotel Id (which is already done) and then create a column that says:

I have a dataframe with two columns, the first one has a date and time (type: datetime64[ns]) and the second column has the timezone that it is in. I cannot figure out how to convert each of the times to UTC based on their individual timezone.

I am looking for a solution to read previous two rows where C_1=104 and next two rows where C_1=105 includes these 2 rows as well. Below are the different dataframe inputs.
The challange I am facing is-