I need to count occurrences of a certain value (let’s assume it’s 3) in a range of columns per each case. To do so I wrote a script as below: First print is: Second: Even though it works fine I am pretty sure there is a more pythonic way to do so. By ‘pythonic’ I mean using native, concise pandas
Tag: python
Sending Protocol Buffer encoded message from Python Server to Java Client
I’m writing a little server that uses protocol buffer to encode some data. TCP Socket is opened between Android Client and Python Server Android Client sends string for processing as normal newline delimited utf-8. Python Server does some processing to generate a response, which gives an Array of Int Arrays: [[int]]. This is encoded in the protocol buffer file: It
This operation is not supported for this document – Sheets API
(<class ‘googleapiclient.errors.HttpError’>, <HttpError 400 when requesting https://sheets.googleapis.com/v4/spreadsheets/1IcMY2TNLYZtGyKO_zcrhP1MudNFXbNdM/values/P%C3%A1gina1%21A%3AP?alt=json returned “This operation is not supported for this document”>, <traceback object at 0x7fbb3dc3bec0>) I am getting this error message when accessing a spreadsheet in Google Sheets, I know that the error occurs because it is hosted on the google drive and is in xlsx format. Does anyone know any alternative to performing this
Occurence of a value in many lists
i have a Series Object in pandas with 2 columns, one for the indices and one with lists, I need to find if a value occurs in only one of these lists and return it with the most optimal way. As an example let’s say we have this i need to return 77 because it occurs in only one of
How to label the line from transform_regression using Altair?
The code below creates a regression line; however, the legend defaults to labeling the line as “undefined.” How can this regression line be labeled in the legend as “reg-line”? Answer Simply add .transform_fold([“reg-line”], as_=[“Regression”, “y”]).encode(alt.Color(“Regression:N”)) after mark line Code should look like
Classifiy dataframe row according to string occurence from a list
With the following dataframe: And the following list: What is the most efficient way to summarize the occurrence of each word from the list in each row of the column ‘Sentence’? I’m looking for the following result: Thanks in advance! Answer You can do it using apply function as well:
Pandas sum() with character condition
I have the following dataframe: I want to use cumsum() in order to sum the values in column “1”, but only for specific variables: I want to sum all the variables that start with tt and all the variable that start with bb in my dataframe, so in the end i’ll have the folowing table : I know how to
pandas sort values to get which item is placed with the most quantity
how to show which item is placed with the most quantity from this data? how to show which item is most ordered groupby choice_description? My data Answer This will list all ties (if any). Output:
Extract corresponding df value with reference from another df
There are 2 dataframes with 1 to 1 correspondence. I can retrieve an idxmax from all columns in df1. Input: Output: df1, df2 and df Now I want to create a df which contains 3 columns Desired Output df: What are the best options to extract the corresponding values from df2? Answer Your main problem is matching the columns between
Python: Random list with odds and even numbers
New to python. I’ve got an assignment where I have to generate a random list of numbers between -10 and 30 and then proceed to call odds and evens from the list. So far I’ve got this, but I have no idea how to proceed and how to make it actually work properly. Also I need to figure out how