(Python)
I want to perform the pct_change() operation in pandas without using the operation.
For example I have an array a = [1, 2, 3, 4]
a.pct_change would result in [NaN, 1.0, 0.5, 0.333]
I want to get the same result without using pct_change().
I attempted doing (a[1:]/a) -1 but don't get the expected result.
(Python) I want to perform the pct_change() operation in pandas without using the operation. For example...
How to make a table from a csv file without using prettytable and without pandas. I have to use format I'm... I'm trying to get a column for "Type", "Total", and "Percent" from TipJoke.csv file. import csv with open('TipJoke.csv', newline='') as csv_file: filereader = csv.reader(csv_file, delimiter=' ') for row in filereader: print( '{:2} {:3} {:4}'.format('Type', 'Total', 'Percent')) print(', '.join(row))
PYTHON: I have a numpy array that holds a name and a phone number such as this one. import numpy as np import pandas as pd LIST = np.array([("James", "Kirk", "512-375-5585"), ("Richard", "Branson, "1234567890"), ("James", "Bond", "34567")]) Then I stuff it into a data frame by doing this df = pd.DataFrame(List, columns=('Firstname', 'Lastname', 'Phone')) How would I go about changing 10 digit phone numbers such as 1234567890 into 123-456-7890 and discarding invalid ones such as 34567 so it reflects in...
How to make a table from a csv file without using prettytable or pandas. I have to use format I'm trying to... I'm trying to get a column for "Type", "Total", and "Percent" from TipJoke.csv file. import csv with open('TipJoke.csv', newline='') as csv_file: filereader = csv.reader(csv_file, delimiter=' ') for row in filereader: print( '{:2} {:3} {:4}'.format('Type', 'Total', 'Percent')) print(', '.join(row))
I want to write a python function to find the minimum I have an nested list: list = [[0,2,3], [1,6],[4,7]] I want to find out in minimum of each list and compare between each other then return the final minimum result for example: above the nested_list [[0,2,3], [1,6],[4,7,11]], for each set of the list the minimum would be [1,5,3] -> final return would be [1]
Python with Pandas dataframe
I have a csv file that contains a large number of columns and
rows. I need to write a script that concatenates some elements of
the first row with some elements of the 2 row. Something like # if
data[1][0] starts with ch then concatenate the element right below
it. I have attached a picture of just a sample of my data. The
booleans have to stay on there as is. But I must drop the...
(PYTHON 3.8) Let's assume I have a list, in which I have two items, both of which are list themselves(without knowing how many integers in each list, but they are the same length). For example: main_list = [[1,2,3],[4,5,6]] main_list[0] = [1,2,3] main_list[1] = [4,5,6] how can I perform operations (take addition for example) on the inner lists to their matching indexes by altering the inner lists but not removing them from main_list(temporary variables are fine) (main_list[0])[0] += (main_list[1])[0] (main_list[0])[1] +=...
In python using numpy and for loops. How would I insert a multidimensional array into another multidimensional array, multiple times. For example if I defined A = [[1,2],[3,4]] and B as a four by four matrix of zeros, How would I insert A into B such that when I print B I get, [[1,2,1,2],[3,4,3,4],[1,2,1,2],[3,4,3,4]]
On Python 3.7.2: How would I make functions for these string functions/methods without using the actual functions? (For example, how would I find if a string is comprised of alphabets without using the function "isalpha()" ?) len() isalpha() isupper() isdigit() swapcase() string_lower()
Python HELP How can a get the diagonals of an n x n list without using numpy. For example if have a list: L = [[1,2,3,4], [5,6,7,8], [9,10,11,12], [13,14,15,16] 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 Then I can get the diagonals: 1, 6, 11, 16 2, 7 , 12 3, 8 5 , 10 ,15 9, 14 2, 5 3, 6, 9 4, 7, 10, 13 8, 11, 14 12,...
Python HELP How can a get the diagonals of an n x n list without using numpy. For example if have a list: L = [[1,2,3,4], [5,6,7,8], [9,10,11,12], [13,14,15,16] 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 Then I can get the diagonals: 1, 6, 11, 16 2, 7 , 12 3, 8 5 , 10 ,15 9, 14 2, 5 3, 6, 9 4, 7, 10, 13 8, 11, 14 12,...