I have a pandas dataframe: Basically, I would like to average the Power for each server but only if the difference is minimum. For example, if you look at the ‘PhysicalWindows1’ server, I have 3 rows, two have a diff of 100, and one has a diff of 500. Since I have two rows with a diff of 100, I
Tag: dataframe
How do I separate measurement value and unit into their respective columns if they appear together in DataFrame?
I have a DataFrame which contains measurements; e.g., weight, height, etc. However, sometimes the measurement column contains units together with values. Therefore, I would like to separate measurement values and units if they are together in DataFrame. Eg., In the below DataFrame, df, the height value and unit of the first entry are in respective columns. However, the value column
Substitute column values of a dataframe with the corresponding items in an array
I have a column in a dataframe which contains an array of numbers from 1 to 5 and I have an array containing five words. I would like to find the simplest, most compact and most elegant way in Python to “in place” replace the numbers in the column with the corresponding words. For example: I am certain that the
Loop through a dataframe, using specific values for individual dates
I have a dataframe that looks like the below. I want to create a new column titled ‘Daily Change’ which will be the result of the first ‘Open’ price of each day divided by the ‘Open’ price for each 5 minute interval. Once the dates changes I need to the first open price of that day and so on. This
Python panda’s dataframe boolean Series/Column based on conditional next columns
I’m having trouble describing exactly what I want to achieve. I’ve tried looking here on stack to find others with the same problem, but are unable to find any. So I will try to describe exactly what I want and give you a sample setup code. I would like to have a function that gives me a new column/pd.Series. This
using a loop to insert values from a column from a data frame into a dictionary key
There are around 60.000 dictionaries stored in a list. There is also a dataframe with the same amount of rows of which I want to take one column and insert into the dictionaries as a key value pair. I have created a for loop which is supposed to update dictionary values, which however seems to take forever. I am looking
Convert nested dict to dataframe, syntax error?
Problem I am converting multiple nested dicts to dataframes. I have a slightly different dict that I haven’t been able to convert to a dataframe using my attempted solution. I am providing a shortened copy of my dict with dummy values as the reprex. Reprex dict: My attempted solution Code is based on similar dict wrangling problems that I had,
Get rid of characters when writing a dataframe to postgress
I have a large script that saves data to a postgres database. Tell me how can I get rid of [‘ and ‘]. I need the data in the storage to be saved without these characters This is how the data looks in the database Tell me how to get rid of these characters, perhaps the problem occurs after parsing
Join two columns of sequentially values
I have dataframe, where ‘A’ 1 – client, B – admin I need to merge messages in row with 1 sequentially and merge lines 2 – admin response sequentially across the dataframe. I do not know how to do this Answer Create groups by consecutive values in B – trick compare shifted values with cumulative sum and aggregate first and
Compare two lists and write for each item corresponding X column value
Let’s say I have a list of users then I have a table What I want is: to have a list of Date for each Resource A, B, C So desired output could be a dictionary: Answer You can use explode then use groupby and agg(list) at the end get the result as dict with to_dict. Output: