Assume I have the dataframe df and I want to slice this in multiple dataframes and store each in a list (list_of_dfs). Each sub-dataframe should only contain the rows “Result”. One sub-dataframe starts, when in column “Point” the value “P1” and in column “X_Y” the value “X” is given. I tried this with first finding the indicies of each “P1”
Tag: split
how do i split a column into two in python on the basis of data in it
for instance the column i want to split is duration here, it has data points like – 110 or 2 seasons, i want to make a differerent column for seasons and in place of seasons in my current column it should say null as this would make the type of column int from string screenshot of my data i tried
Chain df.str.split() in pandas dataframe
Edit: 2022NOV21 How do we chain df.col.str.split() since this returns the split columns if expand = True I am trying to split a column after performing .melt(). If I use assign I end up using the original column and the melted column actually does not even exist. Answer Using expand converts it into a DataFrame, which you do not really
Parse text with uncertain number of fields
I have a file (~50,000 lines) text.txt as below, which contains some gene info from five individuals (AB, BB, CA, DD, GG). The t in the file is a tab seperator. There are also a lot of info that are not useful in the file, and I would like to clean it up. So What I need is to extract
Using Split method or Regex to separate string
In my project I am webscrapping UFC website to gather to the total wins, total losses, and total draws of each UFC athlete. This is part of my code, as I wish to strip the total wins, total losses, and total draws separately: The result is the following: The problem is, I am unable to spew out the total draws.
combining split with findall
I’m splitting a string with some separator, but want the separator matches as well: I can’t find an easy way to combine the 2 lists I get: Into the desired output: Answer From the re.split docs: If capturing parentheses are used in pattern, then the text of all groups in the pattern are also returned as part of the resulting
Python pandas .str.split regex=True ValueError: Columns must be same length as key
I need help with this pandas split with regex. I’m getting the error ValueError: Columns must be same length as key. my column of data is like this my code is desired results would be. Answer Given: Doing: Output: Works fine for me.
Why is the printing order reversed in a simple loop built inside a function(Python) [closed]
Closed. This question is not reproducible or was caused by typos. It is not currently accepting answers. This question was caused by a typo or a problem that can no longer be reproduced. While similar questions may be on-topic here, this one was resolved in a way less likely to help future readers. Closed 9 months ago. Improve this question
How do I split a Pandas DataFrame into sub-arrays (specific use case outlined in detail)?
I apologize for the title, but I don’t know enough to properly condense my question into a single line. Here is the use case: I have a pd.DataFrame with arbitrary index values and a column, ‘timestamp’. I have an ordered List of timestamp values. I want to split the DataFrame into chunks with ‘timestamp’ values that are: less than List[0]
split a string representation with ranges into a list of dates
I have this pandas dataframe column with timeranges (02.07.2021 – 07.07.2021 ) and single days (04.08.2021) as a list. Dates ‘02.07.2021 – 07.07.2021 , 04.08.2021, 19.06.2021 – 21.06.2021’ ‘13.02.2021 – 15.02.2021 , 03.03.2021 ‘ NaN NaN I want this: Dates 02.07.2021, 03.07.2021, 04.07.2021, 05.07.2021, 06.07.2021, 07.07.2021, 04.08.2021, 19.06.2021, 20.06.2021, 21.06.2021 13.02.2021, 14.02.2021, 15.02.2021, 03.03.2021 NaN NaN So basically I want