# Applies the f function to all Row def f(person): print(person.name) df.foreach(f)
Here is what the above code is Doing:
1. It creates a function f that takes a Row object as input.
2. It prints the name of the person.
3. It applies the function f to all the rows in the DataFrame.
from time import sleep sleep(3600) Here is what the above code is Doing: 1. It’s creating a new instance of the class, which is a new object. 2. It’s calling the __init__ method of the class, which is the constructor. 3. It’s calling the __del__ method of the class, which is the destructor. 4. It’s…
from threading import Thread def func1(): print(‘worker 1’) def func2(): print(“worker 2”) if __name__ == ‘__main__’: a = Thread(target = func1) b = Thread(target = func2) a.start() b.start() Here is what the above code is Doing: 1. We are creating two threads, a and b. 2. We are assigning a function to each thread. 3….
>>> ax2 = df.plot.scatter(x=’length’, … y=’width’, … c=’species’, … colormap=’viridis’) Here is what the above code is Doing: 1. We’re using the `plot.scatter()` method to create a scatter plot. 2. We’re passing in the `x` and `y` parameters to specify the columns to plot. 3. We’re passing in the `c` parameter to specify the column…
index = pd.date_range(start=’2020-8-15′, end = ‘2021-8-11′, freq=’M’) print(index) >>>DatetimeIndex([‘2020-08-31’, ‘2020-09-30’, ‘2020-10-31’, ‘2020-11-30’, ‘2020-12-31’, ‘2021-01-31’, ‘2021-02-28’, ‘2021-03-31’, ‘2021-04-30’, ‘2021-05-31’, ‘2021-06-30’, ‘2021-07-31′], dtype=’datetime64[ns]’, freq=’M’) Here is what the above code is Doing: 1. We’re creating a DatetimeIndex object with a start date of 2020-8-15 and an end date of 2021-8-11. 2. We’re setting the frequency to ‘M’,…
# credit to Stack Overflow user in source link import os os.environ[‘TRANSFORMERS_CACHE’] = ‘/set/your/path/here’ Here is what the above code is Doing: 1. We’re importing the os module, which allows us to interact with the operating system. 2. We’re setting the TRANSFORMERS_CACHE environment variable to the path where we want to store the cached models.
users.describe(include=’all’) Here is what the above code is Doing: 1. We’re using the describe method to get a summary of the data. 2. We’re using the include=’all’ parameter to get information on all columns, including those with missing values.