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Tag: merge

Updating A List Word Counter

I’m creating a program that counts letters. I created two dictionaries that both have the same word and, because they are the same exact word, both have the same counter. I want to know how to merge the two dictionaries so that it updates the counters as well, but I consistently receive the result “NONE.” Answer You can concatenate strings

Why do I have more row after the left merge and drop_duplciates()?

iso_selected.shape gives the result: (257, 2) gravity.shapegives the result: (4428288, 79) and I merge them in the following way: gravity1 = gravity.merge(iso_selected, how=”left”, left_on = “iso3_o”, right_on=”iso3″).drop_duplicates() gravity1.shape gives the result: (4571136, 81) Why would I have more rows than 4428288 ? Answer You need remove duplicates before DataFrame.merge by column iso3_o:

Why does pandas.DataFrame.merge return dataframes with different column types than the input dataframes?

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

Similar to pivot table in Python

Here is a dataframe data_1. I want to make this data_1 as follows: I tried pivot_table ,but the output is not the same as I expected. Moreover, I need to save the data_1 as csv file, but the there are no columns id and date in the csv file that I made. Is there any method to change the data_1

Replace column values between two dataframes according to index

I have a dataframe named calls, each call is recorded by a date (calls)[datetime]. each call has an answer status (calls)[Status]. A second Dataframe named NewStatus with same column (NewStatus)[datetime] and the column (NewStatus)[New_Status] that I want to replace in the first dataframe with a date join Desired result is the following for calls : datetime Status 2021-11-22 18:47:02 AB_CL_NO

How to efficiently join a small table to a large one on python

I have two tables similar to these: My goal is to multiply df[‘x’] by df[‘y’] based on id. My current solution works, but it seems to me that there should be a more efficient/elegant way of doing this. This is my code: Answer You can use map to recover the multiplication factor from df_2, then mul to the x column: