I had a dataframe and after applying groupby().sum, I got this outcome. What I have What I want now Things to consider B should remove from the dataframe because 100.00 – 100.00 = 0 Always Buy Amount > Sell Amount How can I achieve this result? Answer I guess it is not optimized way, but you can try this code
Tag: dataframe
Checking segment length in dataframe 1 against multiple segment instances in dataframe 2
Background: I have two Pandas DataFrames: DF1 represents known road segments with >= 7% truck traffic. DF2 represents all road segments in the study area. Columns: SRI is ‘standard route identifier’, MP_START is ‘mile point start’, MP_END is ‘mile point end’, and TRUCK_PCT is ‘truck traffic percentage’. Task: For each row in DF1, the task is to check each record
Average for similar looking data in a column using Pandas
I’m working on a large data with more than 60K rows. I have continuous measurement of current in a column. A code is measured for a second where the equipment measures it for 14/15/16/17 times, depending on the equipment speed and then the measurement moves to the next code and again measures for 14/15/16/17 times and so forth. Every time
How to check if all possible combinations of columns exist in dataframe (Pandas)?
I have the following dataframe And I would like to check if the dataframe is a complete combination of the entries in each column. In the above dataframe this is the case. A = {1,2} B = {1,2,3} and the dataframe contains all possible combinations. Following example would result in a false. The number of columns should be flexible. Many
Extract strings from a Dataframe looping over a single row
I’m reading multiple PDFs (using tabula) into data frames like this: dataframe figure My intention is to use that value ‘330736 1′ into the variable “number” and ’30/09/2015’ into a variable “date”. The issue is that, although these values will always be located in row 1, the columns vary in an unpredictable way across the multiple PDFs. Therefore, I tried
Sampling data from the pandas dataframe
I am trying to sample data from a big dataset. The dataset is like Code to generate a sample dataset The distribution of labels in the dataset is I created a new column in the dataset When I am trying to sample say 5000 items The distribution of the labels in the sampledf is not same as that in the
pandas out of memory error after variable assignment
I have a very large pandas data frame and want to sample rows from it for modeling, and I encountered out of memory errors like this: MemoryError: Unable to allocate 6.59 GiB for an array with shape (40, 22117797) and data type float64 This error is weired since I don’t need allocate such large amount of memory since my sampled
How to sort a dataframe with strings
I got an code running that imports an excel file, and i want to be able to sort some of the data in it and write it to a new excel file. I got the code working somewhat as I want, but can’t make it sort the values as wanted… I want to sort the df from the column named
How to split the columns values separated by commas, into multiple rows and also splitting the total revenue by quantity
if u see the screenshot in that f4,f5, and f9 columns values are separated by commas, i want to split that values into different rows, and f9 is a total number of products, so I need to split the revenue as well based on quantity, for example total number of products according to f9 is 5, so total revenue is
dataframe operations – column attributes to new columns in a new subset dataframe with conditions
I have the dataframe df1 with the columns type, Date and amount. My goal is to create a Dataframe df2 with a subset of dates from df1, in which each type has a column with the amounts of the type as values for the respective date. Input Dataframe: df1 = Desired Output, if the subset of Dates are 2017-02-02 and