I need to calculate Total Hours and Hours by Status per Week using Python / Pandas GROUP BY. I can get Total Hours by each Week: But I don’t know how to also group by Status, so it will be 2 additional columns (On Status Hours and Off Status Hours) If I add Status column just to the groupby part,
Tag: pandas-groupby
Delete the rows that have the same value in the columns Dataframe
I have a dataframe like this : origin destination germany germany germany italy germany spain USA USA USA spain Argentina Argentina Argentina Brazil and I want to filter the routes that are within the same country, that is, I want to obtain the following dataframe : origin destination germany italy germany sp…
Pandas groupby, assign and to_excel – on loop/repeat
I have a dataframe like as shown below My objective is to do the below a) Group columns based on multiple criteria (as shown in below code) b) Assign a default value based on target column. (ex: if target_at50, then assign value 50, if target_at60, then assign 60. if target_at70, then assign 70) b) Repeat the…
How do I find first and last value of each day in pandas dataframe
I have a pandas DataFrame like the below: Price Date 25149.570 2/5/2017 14:22 24799.680 2/5/2017 14:22 24799.680 2/5/2017 14:22 14570.000 2/5/2017 14:47 14570.001 2/5/2017 14:47 14570.001 2/5/2017 14:47 14570.000 2/5/2017 15:01 14570.001 2/5/2017 15:01 14570.001 2/5/2017 15:01 14600.000 2/6/2017 17:49 14600.0…
Is there a faster method to do a Pandas groupby cumulative mean?
I am trying to create a lookup reference table in Python that calculates the cumulative mean of a Player’s previous (by datetime) games scores, grouped by venue. However, for my specific need, a player should have previously played a minimum of 2 times at the relevant Venue for a ‘Venue Preference…
Pandas: using groupby to calculate a ratio by specific values
Hi I have a dataframe that looks like this: and I want to calculate a ratio in the column ‘count_number’, based on the values in the column ‘tone’ by this formula: [‘blue’+’grey’]/’red’ per each unite combination of ‘participant_id’, R…
Pandas groupby counting values > 0
I have a pandas df of the following format I am looking to transform it such that I land up with the below result Essentially for “HIGH_COUNT” and “LOW_COUNT” I want to count the number of occurrences that column was greater than 0, grouped by “MATERIAL”. I have tried to do…
Can we use iterables in pandas groupby agg function?
I have a pandas groupby function. I have another input in the form of dict which has {column:aggfunc} structure as shown below: I want to use this dict to apply aggregate function as follows: Is there some way I can achieve this using the input dict d (may be by using dict comprehensions)? Answer If dictionar…
In Pandas, how to group by column name and condition met, while joining the cells that met the condition in a single cell
I am having a hard time knowing how to even formulate this question, but this is what I am trying to accomplish: I have a pandas datatable with thousands of rows that look like this: id text value1 value2 1 These are the True False 2 Values of “value1” True False 3 While these others False True 4 …
df.to_dict make duplicated index (pandas) as primary key in a nested dict
I have this data frame which I’d like to convert to a dict in python, I have many other categories, but showed just two for simplicity I want the output to be like this Answer You can do this without assigning an additional column or aggregating using list: I created a separate function for readability …