Slightly expanding the Example 1: Merge on Multiple Columns with Different Names, results in the following Python code using Pandas pandas.DataFrame.merge: The resulting output (I’ve added line numbers): Notice the type of a2 and d columns in the resulting df_merge dataframe on lines 24 through 27 have changed from the original int64 to float64. Why would it need to change
Tag: dataframe
How to calculate the Successive Month difference with Groupby in pandas
I have the pandas dataframe, I need to Group by each id and then apply the monthly difference in each id to get monthly frequency number I tried out : Solution : I am expecting the Output dataframe : Answer You can use period objects to calculate the number of monthly periods in between 2 dates: output:
Pandas filtering based on minimum data occurrences across multiple columns
I have a dataframe like this I want those data_fingerprint for where the organisation and country with top 2 counts exists So if see in organization top 2 occurrences are for Tesco,Yahoo and for country we have US,UK . So based on that the output of data_fingerprint should be having What i have tried for organization to exist in my
How to loop over unique dates in a pandas dataframe producing new dataframes in each iteration?
I have a dataframe like below and need to create (1) a new dataframe for each unique date and (2) create a new global variable with the date of the new dataframe as the value. This needs to be in a loop. Using the dataframe below, I need to iterate through 3 new dataframes, one for each date value (202107,
Filter pandas dataframe column and replace values using a list condition
I have the following dataframe: And I have this list of possible acceptable values for everyone that has a type of Contingent Workers: I need to find a way to confirm if everyone under the type “Contingent Worker” have an accetpable value in “Job” and, if not (or blank value), replace that value for “Consultant” resulting in this dataframe: What
Appending data with unequal data frame dimensions
What is the best way to append data using matching column names from two different data frames with differing dimensions? Scenario: Df1 = 350(rows)x2778(columns) Df2 = 321×2910 Df1 has <2778 columns with the exact same name as <2910 columns in Df2. -It could be 500 columns in each data frame as an example that have equivalent names What I want
Pandas: Merge Dataframes Based on Condition but Keep NaN
I have two dataframes, df1 and df2, which I would like to merge on the column ‘id’ where the ‘triggerdate’ from df1 falls between the ‘startdate’ and ‘enddate’ of df2, however, keep the rows where there’s no match. df1: df2: Expected Output: The approach that I have taken so far is: However, this approach does the following 1) Matches the
How to write a function to find clients that are gone, boomeranging, new, etc?
I am trying to come up with a dynamic way to check for the existence of a string and report back a few different results: gone_client, boomerang, new_client. If I groupby address_id and my_date, and the pattern is Verizon, Verizon, Comcast, Comcast, the client left Verizon and went to another company. If the client went from Verizon to Comcast and
How to iterate the loop if the condition is not met
I am trying to get the id of respective movie name in that i need to check whether the url is working or not . If not then i need to append the movie name in the empty list print(movie_buff_uuid) if i passed the data2 in the above loop i am getting this error urllib.error.HTTPError: HTTP Error 404: Not Found
Replacing values in pandas dataframe using nested loop based on conditions
I want to replace the first 3 values with 1 by a 0 if the current row value df.iloc[i,0] is 0 by iterating through the dataframe df. After replacing the values the dafaframe iteration should skip the new added value and start from the next index-in the following example from index 7. If the last tow values in the dataframe