Given a string, print its even-indexed and odd-indexed characters as space-separated strings on a single line. Example: s = adbecf => Print abc def My approach: Answer No need to use complex ways. here is a easy way to do it. Input: adbecf Output: abc def
Tag: join
pandas join tables on two columns without ordering of values
I would like to achieve what it’s described here: stackoverflow question, but only using standard pandas. I have two dataframes: Fist Second: I want to join the two dataframes such that my final dataframe is identical to the first one, but it has also the book_count column with the corresponding values …
add a suffix when col names are similar
I am merging two dataframes and both of them have a col called “man”. After the join, one col is called “man_x” and the second is called “man_y”. Is it possible to append the table name or any other string instead of x, y when column names are the same? After this, If I add…
Merging time series data so that column values are fitted into dictionaries
I have two time-series data frames that track the same certain countries throughout the same amount of time, but the variables they track for each observation represent vastly different things. For example, the first data frame is like so: Tracking variable ‘A’: Country 01/01/2020 01/02/2020 01/03…
Pandas merge indexing not behaving as expected
I am trying to perform an anti-join in effectively one line. However, my one line solution is not giving me the same results that a receive when breaking up the code into two lines (which behaves as expected). Specifically, the single-line solution results in a dataframe with fewer rows. The goal of my anti-j…
How to use JOIN and SELECT AS together in SQLAlchemy?
I have the two following tables. Users Table id name email 32 Hello e@mail.com 23 World p@mail.com Sales Table id SellerId CustomerId Amount 4 32 23 25 I want to join the tables in the following way to get this result. Here I want to only get the entries where customer id is equal to 23. Id SellerId SellerNam…
How to join on multiple columns in Pyspark?
I am using Spark 1.3 and would like to join on multiple columns using python interface (SparkSQL) The following works: I first register them as temp tables. I would now like to join them based on multiple columns. I get SyntaxError: invalid syntax with this: Answer You should use & / | operators and be ca…
Using Python Pandas to bin data in one df according to bins defined in a second df
I am attempting to bin data in one dataframe according to bins defined in a second dataframe. I am thinking that some combination of pd.bin and pd.merge might get me there? This is basically the form each dataframe is currently in: df: And this is the table with the bins, df2: I would like to match the bin, a…
How to do/workaround a conditional join in python Pandas?
I am trying to calculate time-based aggregations in Pandas based on date values stored in a separate tables. The top of the first table table_a looks like this: Here is the code to create the table: The second table, table_b, looks like this: and the code to create it is: I want to be able to get the sum of