# Excel to Python

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- Importing
- Plotting
- Statistical analysis



## **How Excel Translates to Python**

Here’s how common Excel functionalities map to Python:

| **Excel Feature**       | **Python Equivalent**                                    |
| ----------------------- | -------------------------------------------------------- |
| Formulas (SUM, AVERAGE) | `numpy`, `pandas` (`df.sum()`, `df.mean()`)              |
| Sorting & Filtering     | `pandas.sort_values()`, `df[df['col'] > value]`          |
| Conditional Formatting  | `matplotlib` for highlighting                            |
| Pivot Tables            | `pandas.pivot_table()`                                   |
| Charts & Graphs         | `matplotlib`, `seaborn`, `plotly`                        |
| Regression Analysis     | `scipy.stats.linregress`, `sklearn.linear_model`         |
| Solver/Optimization     | `scipy.optimize`                                         |
| VBA Macros              | Python scripting with `openpyxl`, `pandas`, or `xlwings` |

## Statistical functions

#### SUM
Built-in:
```python
my_array = [1, 2, 3, 4, 5]
total = sum(my_array)
print(total)  # Output: 15
```
Numpy:
```python
import numpy as np

my_array = np.array([1, 2, 3, 4, 5])
total = np.sum(my_array)
print(total)  # Output: 15
```

### Average
Built-in:
```python
my_array = [1, 2, 3, 4, 5]
average = sum(my_array) / len(my_array)
print(average)  # Output: 3.0
```
Numpy:
```python
import numpy as np

my_array = np.array([1, 2, 3, 4, 5])
average = np.mean(my_array)
print(average)  # Output: 3.0
```



## Plotting
We can use the package *matplotlib* to plot our graphs in python. Matplotlib provides data visualization tools for the Scientific Python Ecosystem. You can make very professional looking figures with this tool.

Here is a section from the matplotlib documentation page that you can run in python.
```python
import matplotlib.pyplot as plt

fig, ax = plt.subplots()             # Create a figure containing a single Axes.
ax.plot([1, 2, 3, 4], [1, 4, 2, 3])  # Plot some data on the Axes.
plt.show()                           # Show the figure.
```

Check out the documentation pages for a [simple example](https://matplotlib.org/stable/users/explain/quick_start.html#a-simple-example) or more information on the types of plots you came create [here](https://matplotlib.org/stable/plot_types/index.html).