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Introducing Matplotlib #727

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30 changes: 9 additions & 21 deletions contrib/plotting-visualization/matplotlib-introduction.md
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Expand Up @@ -12,8 +12,9 @@ To make this process of data visualization easier and clearer, matplotlib librar

## Starting with Matplotlib

### 1.] Install and import the neccasary libraries - mayplotlib.pylplot
```python
### 1. Install and import the neccasary libraries - mayplotlib.pylplot

```bash
pip install matplotlib
```

Expand All @@ -22,9 +23,7 @@ import maptplotlib.pyplot as plt
import numpy as np
```



### 2.] Scatter plot
### 2. Scatter plot
Scatter plot is a type of plot that uses the cartesian coordinates between x and y to describe the relation between them. It uses dots to represent relation between the data variables of the data set.

```python
Expand All @@ -41,12 +40,9 @@ plt.tight_layout()
plt.show()
```

![scatterplot](images/scatterplot.png)


![scatterplot](https://github.com/Harshita297/learn-python/assets/122027571/aa57eb31-4377-4f75-9a97-e4fa7a54a938)


### 3.] Bar plot
### 3. Bar plot
Bar plot is a type of plot that plots the frequency distrubution of the categorical variables. Each entity of the categoric variable is represented as a bar. The size of the bar represents its numeric value.

```python
Expand All @@ -61,11 +57,10 @@ plt.ylabel("Y values")

plt.show()
```
![barplot](https://github.com/Harshita297/learn-python/assets/122027571/00cea3cd-a962-4bfe-b158-921389ee564c)


![barplot](images/barplot.png)

### 4.] Histogram
### 4. Histogram
Histogram is the representation of frequency distribution of qualitative data. The height of each rectangle defines the amount, or how often that variable appears.

```python
Expand All @@ -79,14 +74,7 @@ plt.ylabel("Frequency Distribution")

plt.show()
```
![histogram](https://github.com/Harshita297/learn-python/assets/122027571/32470819-bac5-4bb2-9f36-79521fa40bf3)








![histogram](images/histogram.png)