In this short guide, you’ll see how to get started with **Pandas**.

To begin, install Pandas using this command:

pip install pandas

## Import pandas as pd

In order to use the Pandas package in Python, you’ll need to type **“import pandas as pd”** at the top of your code.

You’ll then be able to use “**pd**” to access various “**pandas**” functions and objects throughout your code.

Here is an example that demonstrates how to **“import pandas as pd”** and then use it to create a DataFrame with 2 columns:

import pandas as pd # Define the data data = { "Product": ["Laptop", "Tablet", "Smartphone", "Headphones", "Printer"], "Price": [1000, 300, 850, 150, 200] } # Create the DataFrame df = pd.DataFrame(data) # Print the DataFrame print(df)

The resulted DataFrame:

```
Product Price
0 Laptop 1000
1 Tablet 300
2 Smartphone 850
3 Headphones 150
4 Printer 200
```

### Calculate the total sum

You can use **“sum()”** in order to calculate the total sum for the “**Price**” column:

import pandas as pd # Define the data data = { "Product": ["Laptop", "Tablet", "Smartphone", "Headphones", "Printer"], "Price": [1000, 300, 850, 150, 200] } # Create the DataFrame df = pd.DataFrame(data) # Calculate the total sum total_sum = df["Price"].sum() # Print the total sum print(total_sum)

The total sum is:

`2500`

### Calculate the mean (average)

Use **“mean()”** to calculate the mean (average) for the “**Price**” column:

import pandas as pd # Define the data data = { "Product": ["Laptop", "Tablet", "Smartphone", "Headphones", "Printer"], "Price": [1000, 300, 850, 150, 200] } # Create the DataFrame df = pd.DataFrame(data) # Calculate the mean price mean_price = df["Price"].mean() # Print the mean price print(mean_price)

The resulted mean is:

`500`