I have a dataframe df Cat B_1 A_2 C_3 A 1 2 3 B 4 5 6 C 7 8 9 which I want to convert into a dataframe so that the rows in column
I have two dataframes A B 0 1 2 1 1 2 2 1 2 and C D 0 1 4 1 2 5 2 3 6 I need the mean of the cross products (AC, AD, BC, BD).
Here is my code block: import pandas as pd import datetime as dt first_day = dt.date(todays_year, todays_month, 1) print(first_day) >2021-02-01 print(type(
Don't understand why I can't do even the most simple data manipulation with this data i've scraped. I've tried all sorts of methjods to manipulate the data but
I have generated a DF from the below code: url='https://www.rootsandrain.com/event4493/2017-aug-26-uci-world-cup-dh-7-val-di-sole/results/' response = requests.
I have this dataframe: identifier_1 measure Value identifier_2 abc height 12 oii abc weig
I have a dataframe like this: JoiKey period Age Amount Jk1 2022-02 2 200 Jk1 2022-02 3 450 Jk2 2022-03 5 500 Jk3 2022-03 0 200 Jk2 2022-02 8 300 Jk3 2022-03 9
Given column in the csv file labels ['N'] ['C'] ['D'] ['A'] ['D','C'] ['H'] ['D','G'] ['M'] ['O'] I want the labels a
UPDATE: I'm getting a strange result in the outcome. Occasionally, the earliest date of the result show after 2 or 3 etc times for example Item Kg Date_1 Price
I recently transitioned from using SQLite for most of my data storage and management needs to MySQL. I think I've finally gotten the correct libraries installed
Is there a more sophisticated way to check if a dataframe df contains 2 columns named Column 1 and Column 2: if numpy.all(map(lambda c: c in df.columns, ['Colum
I have a list of dict containing x and y. I want to make x the index and y the column headers. How can I do it? import pandas pt1 = {"x": 0, "y": 1, "val": 3,}
I have a dataframe contains orders data, each order has multiple packages stored as comma separated string [package & package_code] columns I want to split
I assume this is an easy fix and I'm not sure what I'm missing. I have a data frame as such: index c1 c2 c3 2015-03-07 01:2
I understand that to drop a column you use df.drop('column name', axis=1). Is there a way to drop a column using a numerical index instead of the column name?
I have a dataframe: df- A B C D E 0 V 10 5 18 20 1 W 9 18 11 13 2 X 8 7 12 5 3 Y 7 9 7 8 4 Z 6 5 3 90
The College Football Database (cfbd) contains all team ranks for each week of every college football season going back to 1937.I am trying to set up data from t
I have a dataframe: df- A B C D E 0 V 10 5 18 20 1 W 9 18 11 13 2 X 8 7 12 5 3 Y 7 9 7 8 4 Z 6 5 3 90
Given the following DataFrame of pandas in Python: | ID | date | |--------------|------------------------------------
I have a very large dataframe (around 1 million rows) with data from an experiment (60 respondents). I would like to split the dataframe into 60 dataframes (a d