Consider the following data frames in Python Pandas: DataframeA ColA ColB ColC 1 dog 439 1 cat 932 1 frog 932 2 dog 2122 2 cat 454 2 frog 773 3 dog 9223 3 cat 3012 3 frog 898 DataframeB ColD ColE 1 101 2 314 3 124 To note, ColB just repeats it’s string values as ColA iterates upwards.
Tag: pandas
How to calculate average returns over separate consecutive ranges determined by another column in Python?
I currently have a Pandas DataFrame which contains a time series of asset prices and a column containing a “state”. There are three states -1, 0, 1 that occur at various points in the data. I am trying to find the average return on the asset in each of these states, ideally using a vectorised meth…
Python/Pandas:How to process a column of data like a dictionary
i have a csv lie this i would like to sum the values from column “PDCP.RxBytesUl”, PDCP.RxBytesUl = 5QI1+5QI2+5QI3+5QI4+5QI5+5QI6+5QI7+5QI8+5QI9 finally,the result is like this At first I wanted to convert this column into a dict(), but I found the format was not right, i have no idea, please help…
pandas replace values in reference to a user input
I am stuck a little bit, hope you can help me, I want to replace a value in a pandas df according to a input Pandas df contains 3 string columns and the default value for category is always 1 Area Name Category Sales Tom 1 Finance Laura 1 Finance An 1 Ops Roger 1 I have a dict= {‘finance’:’2…
Python – How to clean time series data
I have a df which looks like this: I’m trying to create a new column called ‘First_Contract’: ‘First_Contract’ needs to take the third-last value of ‘Sep’ column, before ‘Sep’column reaches NaN. The subsequent values need to be filled with ‘Dec’…
Grouping data in a manner to export them as a CSV file
I have a messy data which seems like I want to group them in a way that they would look like I tried mystr.split() to end up in a list and then define the following function to group them in 3’s: I was pretty sure that was going to work, however, I got the following output: I don’t know why
How to fill in missing values in Pandas dataframe according to pattern in column?
Suppose I have a dataframe with a column as follows: I want each row to be filled in with increments of 5 so that the final output would appear like: I’ve tried using np.arange and .reindex() but haven’t had much luck. I’m looking for an iterative approach instead of simply manually filling …
Pandas columns created function on Groupby sorted columns
I have a dataframe like below. What i am trying to do is calculate a column E1 and F1 with a sort and group by then return the entire data frame. The B1 column is incremental, but not necessarily by 1, but the sort on B1 will be if i only had one A1 value like my workflow is Which
list in dictionary get empty out when coming out of the loop
This is the code I wrote for web scraping purposes. I want to save all data in the dictionary and then save that data into a dataframe. Up to the last iteration, it saves the dictionary, but when coming out of the loop all lists (that are the values of my dictionary) are empty. How can one fix that? This
How to downcast numeric columns in Pandas?
How to optimize the data frame memory footprint and find the most optimal (minimal) data types dtypes for numeric columns. For example: Expected result: Answer You can use parameter downcast in to_numeric with selectig integers and floats columns by DataFrame.select_dtypes, it working from pandas 0.19+ like m…