kopia lustrzana https://github.com/animator/learn-python
Update matplotlib-introduction.md
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@ -12,8 +12,9 @@ To make this process of data visualization easier and clearer, matplotlib librar
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## Starting with Matplotlib
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## Starting with Matplotlib
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### 1.] Install and import the neccasary libraries - mayplotlib.pylplot
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### 1. Install and import the neccasary libraries - mayplotlib.pylplot
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```python
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```bash
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pip install matplotlib
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pip install matplotlib
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```
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```
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@ -22,9 +23,7 @@ import maptplotlib.pyplot as plt
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import numpy as np
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import numpy as np
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```
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```
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### 2. Scatter plot
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### 2.] Scatter plot
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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.
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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.
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```python
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```python
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@ -41,12 +40,9 @@ plt.tight_layout()
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plt.show()
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plt.show()
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```
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```
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### 3. Bar plot
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### 3.] Bar plot
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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.
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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.
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```python
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```python
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@ -61,11 +57,10 @@ plt.ylabel("Y values")
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plt.show()
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plt.show()
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```
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```
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### 4. Histogram
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### 4.] Histogram
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Histogram is the representation of frequency distribution of qualitative data. The height of each rectangle defines the amount, or how often that variable appears.
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Histogram is the representation of frequency distribution of qualitative data. The height of each rectangle defines the amount, or how often that variable appears.
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```python
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```python
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@ -79,14 +74,7 @@ plt.ylabel("Frequency Distribution")
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plt.show()
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plt.show()
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```
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```
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