if 10000 <= number <= 30000:
Here is what the above code is Doing:
1. It's checking if the number is between 10000 and 30000.
2. If it is, it's printing out the number.
3. If it isn't, it's printing out "The number is outside the range."
sys.stdout.flush() os.execl(sys.executable, ‘python’, __file__, *sys.argv[1:]) Here is what the above code is Doing: 1. It’s printing a message to the console. 2. It’s flushing the output buffer. 3. It’s executing itself again with the same command line arguments. The result is an infinite loop of the program printing the message and then executing itself again….
AttributeError: ‘DataFrame’ object has no attribute ‘data’ Here is what the above code is Doing: 1. We’re creating a new DataFrame called df_new. 2. We’re using the .loc[] method to select the rows and columns we want. 3. We’re using the .data attribute to access the underlying NumPy array. The .data attribute is a NumPy…
from pytube import Playlist p = Playlist(‘https://www.youtube.com/playlist?list=PLGo0NLnuNoa-KKJPn8ZBRjksb8jaw4lz-‘) print(f’Downloading: {p.title}’) for video in p.videos: print(video.title) st = video.streams.get_highest_resolution() st.download() #video.streams.first().download() Here is what the above code is Doing: 1. We create a Playlist object by passing the URL of the playlist to the constructor. 2. We print the title of the playlist. 3. We iterate over…
a = (‘tree’, ‘plant’, ‘bird’) b = (‘ocean’, ‘fish’, ‘boat’) # a and b are both tuples c = a + b # c is a tuple: (‘tree’, ‘plant’, ‘bird’, ‘ocean’, ‘fish’, ‘boat’) Here is what the above code is Doing: 1. It creates a tuple called a and assigns it the values ‘tree’, ‘plant’,…
import os import sys import subprocess from optparse import OptionParser from datetime import datetime import boto from boto.s3.key import Key DB_USER = ‘databaseuser’ DB_NAME = ‘databasename’ BACKUP_PATH = r’/webapps/myapp/db_backups’ FILENAME_PREFIX = ‘myapp.backup’ # Amazon S3 settings. AWS_ACCESS_KEY_ID = os.environ[‘AWS_ACCESS_KEY_ID’] AWS_SECRET_ACCESS_KEY = os.environ[‘AWS_SECRET_ACCESS_KEY’] AWS_BUCKET_NAME = ‘myapp-db-backups’ def main(): parser = OptionParser() parser.add_option(‘-t’, ‘–type’, dest=’backup_type’, help=”Specify either…
import numpy as np import pandas as pd df[‘YourColumn’] = df[‘TanhResult’].apply(lambda x: np.tanh(x)) Here is what the above code is Doing: 1. Create a new column called ‘YourColumn’ 2. Apply the lambda function to the ‘TanhResult’ column 3. The lambda function takes the value of the ‘TanhResult’ column and applies the tanh function to it…