I have an array of dimensions (9131,101,191). The first dimension is the days from 1/1/2075 till 31/12/2099. I want to extract all the days which are in the month of July. How can I do this in xarray? I have tried using loops and numpy but not getting the desired result. Ultimately, I want to extract all the arrays which
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I am trying to perform a web automation testing, and now i am stucking at how to select random values from the outlet and time list. Kinda ran out of idea, hope someone could help, Thanks in Advance and Have a Nice day. Answer As far as I understand the code above, something like this should work:
Login method using MySql.connector not working properly
I created a a method in pythin so that user could login as a user or as an admin but the program is not working as I expected it to be, I am posting the whole program, but mainly the error is coming in login method as I am not able to create a proper logic required for the method.
from dataframe to the body of Email automatically,several formatting issues: thousand separator, color(red for negative number and green for positive)
I have a dataframe look like this I wish to send it as the BODY of the Email with Outlook, it would be great to automate it in the future (as daily report without human intervention) but for the moment I just struggle to achieve some formatting how to get it directly to the body of Email or I have
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After doing some research I understood that pandas can give us better performace comparing to openpyxl. I’m trying to convert this code from openpyxl to pandas: Anyone can give me a suggestion about how to convert this code? Answer Here is the equivalent code using pandas: This code uses pandas to read the data from the “VendorInfo” sheet into a
how to transform dataframe into data set/object
I have a data set in a dataframe that’s almost 9 million rows and 30 columns. As the columns count up, the data becomes more specific thus leading the data in the first columns to be very repetitive. See example: park_code camp_ground parking_lot acad campground1 parking_lot1 acad campground1 parking_lot2 acad campground2 parking_lot3 bisc campground3 parking_lot4 I’m looking to feed that
I want to convert file data into 3d dictionary using python
Like I want this type of dictionary by reading file: or this will be enough. I have a file lets name file.txt which has data like I am trying but i dint get the result this following is my try: it gives me output {‘A’: ‘7’, ‘B’: ‘8’, ‘C’: ‘9’} I know its obvious it will not give me 3d
Slice Dataframe in sub-dataframes when specific string in column is found
Assume I have the dataframe df and I want to slice this in multiple dataframes and store each in a list (list_of_dfs). Each sub-dataframe should only contain the rows “Result”. One sub-dataframe starts, when in column “Point” the value “P1” and in column “X_Y” the value “X” is given. I tried this with first finding the indicies of each “P1”
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I have 2 dataframes, the first is a small dataframe (df1) with information to use to fill a field (named Flag) of the second dataframe (df2). I need to write a function that uses each row of df1 as parameters to fill each row of df2 with a certain value (Y or N). df1 = type q25 q75 A 13
SKLearn & ElasticNet: Cross validation fails when using Accuracy as a metric
I have a binary classification problem. I’ve been using cross validation to optimize the ElasticNet parameters. However ElasticNet only seems to work when I supply roc_auc as the scoring method to be used during CV, However I also want to test out a wide range of scoring methods, in particular accuracy. Specifically, when using accuracy, ElasticNet returns this error: However