Could you teach our Lovelace Series audience something technical in less than 5 minutes?
Sure! Here is how to set-up a python virtual env and plot a graph:
Setting up a Virtual Environment:
1. Open your terminal or command prompt.
2. Navigate to the directory where you want to create your project using the `cd` command.
3. Create a new virtual environment by running:
```python -m venv myenv```This creates a new directory called `myenv` containing the virtual env.
4. Activate the virtual env:
- On Windows: `myenv\Scripts\activate`
- On Unix/Linux: `source myenv/bin/activate`
Your terminal now shows `(myenv)` at the start to show the virtual env is active.
Installing Jupyter Notebook and Libraries:
Now we want to install soem libraries to help us plot a graph:
5. Install Jupyter Notebook, pandas, and matplotlib by running:
```pip install jupyter pandas matplotlib```Creating a Notebook with "Hello World" and Plotting CSV data into a graph:
6. Run the following command to start the Jupyter Notebook server:
```jupyter notebook```This should open a new tab or window in your browser with Jupyter labs interface.
7. In the Jupyter interface, click "New" > "Python 3" to create a new notebook.
8. In the new notebook, create a code cell by clicking on the "+" icon or using the keyboard shortcut.
9. In the code cell, type the following:
```pythonprint("Hello World!")```10. Run the code cell by clicking the "Run" button or pressing Shift+Enter.
You should see the output "Hello World!" printed below the code cell.
11. Create a new code cell and follow these steps to plot a graph using CSV data:
a. Import the required libraries:
```python import pandas as pd import matplotlib.pyplot as plt ```b. Read the CSV data into a pandas DataFrame:
```python df = pd.read_csv('data.csv') ```Replace `'data.csv'` with the name of your CSV file.
c. Create a new figure with a specific size:
```python plt.figure(figsize=(8, 6)) ```d. Create a scatter plot using the data from the DataFrame:
```python plt.scatter(df['x'], df['y']) ```Replace `'x'` and `'y'` with the column names in your CSV file that contain the x and y data, respectively.
e. Add labels to the x and y axes:
```python plt.xlabel('X Label') plt.ylabel('Y Label') ```f. Add a title to the plot:
```python plt.title('My Scatter Plot') ```g. Display the plot:
```python plt.show() ```12. Run the code cell with the plotting code, and you’ll see the scatter plot rendered in the output area of your notebook.
Enjoy!
Note: Make sure your CSV data is in the same directory as your notebook or use the correct file path when reading the data using `pd.read_csv()`.
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