Report_Card.loc[:,"Grades"] The first argument ( : ) signifies which rows we would like to index, and the second argument (Grades) lets us index the column we want
Here is what the above code is Doing:
1. We are selecting the column named Grades from the DataFrame named Report_Card
2. We are then assigning the column to a variable named Grades
3. We are then printing the variable Grades
Write a program that repeatedly prompts a user for integer numbersOnce ‘done’ is entered, Print out the largest and smallest of the numbers entered Here is what the above code is Doing: 1. We are creating a list of numbers 2. We are using a while loop to keep asking the user for a number…
import datetime datetime.datetime.utcnow().isoformat() >>> 2020-03-20T01:30:08.180856 Here is what the above code is Doing: 1. We import the datetime module. 2. We call the datetime.datetime.utcnow() function to get the current UTC time. 3. We call the isoformat() method on the datetime object to get a string representation of the time.
(x or y) == (y if not x else x) Here is what the above code is Doing: 1. If x is true, then return x. 2. If x is false, then return y. The above code is equivalent to: def logical_or(x, y): if x: return x else: return y
conda config –get channels #——-Output————-# –add channels ‘defaults’ # lowest priority –add channels ‘https://pypi.org/project/librosa/’ –add channels ‘intel’ # highest priority #————————–# conda config –remove channels ‘https://pypi.org/project/librosa/’ Here is what the above code is Doing: 1. It’s getting the current list of channels. 2. It’s adding a new channel to the list. 3. It’s removing a…
import calendar import datetime now = datetime.datetime.now() print calendar.monthrange(now.year, now.month)[1] 29 Here is what the above code is Doing: 1. import calendar 2. import datetime 3. now = datetime.datetime.now() 4. print calendar.monthrange(now.year, now.month)[1] 1. import calendar This imports the calendar module. 2. import datetime This imports the datetime module. 3. now = datetime.datetime.now() This creates…
In [55]: import pandas as pd equiv = {7001:1, 8001:2, 9001:3} df = pd.DataFrame( {“A”: [7001, 8001, 9001]} ) df[“B”] = df[“A”].map(equiv) print(df) A B 0 7001 1 1 8001 2 2 9001 3 [3 rows x 2 columns] Here is what the above code is Doing: 1. Create a dictionary that maps the values…