Convert pandas dataframe from wide to long
I have a pandas.Dataframe with the following columns:
I have a pandas.Dataframe with the following columns:
My df looks as follows:
I’m working with some datetime data in a dataframe. It’s in a format day/month/year Ex: Date —————- 27/06/2021 00:00 27/06/2021 00:00 30/06/2021 00:00 30/06/2021 00:00 30/06/2021 00:00 18/06/2021 00:00 26/06/2021 00:00 28/06/2021 00:00 28/06/2021 00:00 27/06/2021 00:00 28/06/2021 00:00 30/06/2021 00:00 12/06/2021 00:00 28/06/2021 00:00 I want to extract the month and year, so I … Read more
I have a Pandas DataFrame containing the date that a stream gage started measuring flow and the date that the station was decommissioned. I want to generate a plot showing these dates graphically. Here is a sample of my DataFrame:
I have a datetime column as below –
I read a csv file containing 150,000 lines into a pandas dataframe. This dataframe has a field, Date, with the dates in yyyy-mm-dd format. I want to extract the month, day and year from it and copy into the dataframes’ columns, Month, Day and Year respectively. For a few hundred records the below two methods work ok, but for 150,000 records both take a ridiculously long time to execute. Is there a faster way to do this for 100,000+ records?
It appears that the pandas read_csv function only allows single character delimiters/separators. Is there some way to allow for a string of characters to be used like, “*|*” or “%%” instead?
I would like to read in an excel spreadsheet to python / pandas, but have the formulae instead of the cell results.
So I have initialized an empty pandas DataFrame and I would like to iteratively append lists (or Series) as rows in this DataFrame. What is the best way of doing this?