Pandas: Find closest date – without set_index – multiple conditions
We have the following Pandas Dataframe:
Python
Imposing constraints on all (numbered) diagonals in CVXPY
I am looking to implement a constraint on an optimization on all diagonals of a matrix using CVXPY. The diag function in CVXPY only returns the main diagonal. Is there a simple way to implement the numbered diagonal function in numpy using a CVXPY variable, in order to iterate over all diagonals adding a constraint for each?
Plot attribute missing from matplotlib
—-> 4 import matplotlib.plot as plt
5 import seaborn as sns
POST on MYSQL database done in terminal but nothing in my base
I would like to know why all seems to be okay but nothing is insert in my mysql database ?
I get some data from an api and I would like to insert data in table.
Python Pandas – How can I make .replace function work with dict and conditionals?
I’m trying to change a .CSV row data. So for the new data I have a dict. I want to say python that if the keys in my dict are equal to the items row in my .csv then change the data in another row.
pandas dataframe groupby sum returns wrong answer
I am trying to groupby a dataframe with 4000+ rows by ‘summing’ a column called ‘From Email Address’.
trying to send data from one script in python to another script
I am trying to write a script so when an IP address can’t be seen a message gets sent with a telegram letting me know which computer is offline
How can I get automatical features with dfs, using featuretools, when I have only one dataframe?
I am trying to figure out how Featuretools works and I am testing it on the Housing Prices dataset on Kaggle. Because the dataset is huge, I’ll work here with only a set of it.
How to read JSON that has values in parenthesis with data type?
I have JSON file built like the following:
How to create a new dataframe column with a set of nested IF rules (apply is very slow)
What I need I need to create new columns in pandas dataframes, based on a set of nested if statements. E.g. if city == 'London' and income > 10000: return 'group 1' elif city == 'Manchester' or city == 'Leeds': return 'group 2' elif borrower_age > 50: return 'group 3' else: return 'group 4' This … Read more