# Ascii graph in python

When working with ASCII graphs in Python, there are several ways to achieve the desired output. In this article, we will explore three different approaches to solve this problem.

## Approach 1: Using ASCII Art Library

One way to create ASCII graphs in Python is by using an ASCII art library. These libraries provide functions and methods to generate ASCII art from given data. One popular library is the `art` library, which can be installed using pip:

``pip install art``

Once installed, we can use the library to create ASCII graphs. Here’s an example:

``````from art import *

data = [1, 2, 3, 4, 5]
graph = text2art(str(data))
print(graph)``````

This will generate an ASCII graph representing the given data. The `text2art()` function converts the data into ASCII art, and the resulting graph is printed to the console.

## Approach 2: Manual ASCII Graph Generation

If you prefer a more manual approach, you can generate ASCII graphs by writing your own code. Here’s an example:

``````data = [1, 2, 3, 4, 5]

max_value = max(data)
graph = ""

for value in data:
normalized_value = int(value / max_value * 10)
graph += "#" * normalized_value + "n"

print(graph)``````

In this code, we first find the maximum value in the data list. Then, we iterate over each value and normalize it to a scale of 10. We multiply the normalized value by “#” to represent the data point in the graph. Finally, we print the graph to the console.

## Approach 3: Using Matplotlib Library

If you are working with more complex data and want to create professional-looking ASCII graphs, you can use the `matplotlib` library. This library is primarily used for data visualization, but it also provides functionality to generate ASCII graphs. Here’s an example:

``````import matplotlib.pyplot as plt

data = [1, 2, 3, 4, 5]

plt.bar(range(len(data)), data)
plt.show()``````

This code uses the `bar()` function from `matplotlib.pyplot` to create a bar graph from the given data. The resulting graph is displayed using the `show()` function.

After exploring these three approaches, it is clear that the best option depends on the specific requirements of your project. If you need a simple ASCII graph, the manual approach (Approach 2) might be sufficient. However, if you require more advanced features or want to create professional-looking graphs, using a library like `art` or `matplotlib` (Approach 1 or 3) would be a better choice.

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### 7 Responses

Approach 3 is cool, but Im all about that old-school ASCII art library from Approach 1!

2. Ayan Lara says:

Approach 2 seems like a fun challenge, but Approach 3 with Matplotlib might be more versatile. What do you think?

1. Baylor Burton says:

I totally disagree. Approach 2 is way more practical. Matplotlib is a nightmare to work with and overcomplicates things. Stick to simplicity, my friend.

3. Lyric says:

Approach 2 seems fun and creative, but Approach 1 and 3 sound more efficient. What do you guys think? 🤔

I totally disagree! Approach 2 is the way to go! It injects some much-needed excitement into the process. Efficiency is overrated. Lets embrace creativity and have a little fun for once. Lifes too short to always take the efficient route.

4. Sloane says:

Approach 3 wins the ASCII graph game hands down! Matplotlib rocks! 🎉🐍

5. Samuel says:

Approach 1 seems cool, but is using a whole library necessary? 🤔 #SimplicityMatters