Task-Python Packages

Few Python Packages

Progress Bar and TQDM:
To implement progress bars for tasks such as loops, file processing, or downloads.

from progress.bar import ChargingBar
bar = ChargingBar('Processing', max=20)
for i in range(20):
    # Do some work
    bar.next()
bar.finish()

Output:

Processing ████████████████████████████████ 100%

TQDM: Similar to progress bar but its more simple to setup than progress bar.

from tqdm import tqdm
import time

for i in tqdm(range(100)):
    time.sleep(0.1)

Output:

100%|██████████████████████████████████████| 100/100 [00:00



<p><strong>Matplotlib:</strong></p>

<p>Matplotlib is used for creating static, animated, and interactive visualizations.<br>
</p>

<pre class="brush:php;toolbar:false">import matplotlib.pyplot as plt

x = [1, 2, 3, 4, 5]
y = [2, 4, 6, 8, 10]

plt.plot(x, y, label='Linear Growth', color='blue', linestyle='--', marker='o')
plt.title("Line Plot Example")
plt.xlabel("X-axis")
plt.ylabel("Y-axis")
plt.legend()
plt.show()

Output:

Numpy:
NumPy (Numerical Python) is a fundamental Python library for numerical computing. It provides support for working with large, multi-dimensional arrays (like 1-D,2-D,3-D) and matrices, along with a collection of mathematical functions to operate on these arrays efficiently.

Example:

import numpy as np

# 1D array
arr1 = np.array([1, 2, 3, 4])

# 2D array
arr2 = np.array([[1, 2], [3, 4]])

print(arr1, arr2)

Output:

[1 2 3 4] [[1 2]
 [3 4]]

Pandas:
It is used for data manipulation and analysis with Series(lists) and DataFrame(table or spreadsheet).

Example:

import pandas
x=[1,2,3]
y=pandas.Series(x,index=["no1","no2","no3"])
print(y)

Output:

no1    1
no2    2
no3    3
dtype: int64

The above is the detailed content of Task-Python Packages. For more information, please follow other related articles on the PHP Chinese website!