> For the complete documentation index, see [llms.txt](https://otd.gitbook.io/book/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://otd.gitbook.io/book/appendix/table-utilities.md).

# Table Utilities

In order to make it easier for you to visualize tables and create graphs, we've created a few utility functions! The following describe what they do and how they work.

### visualize\_table(table)

This function takes in a table and displays it! For example, the table:

| Fruit    | Price |
| -------- | ----- |
| "apple"  | 1.49  |
| "orange" | 1.49  |
| "peach"  | 2.49  |

Can be written as:

```python
fruit = {
    'fruit': 
        ['apple', 'orange', 'peach'], 
    'price': 
        [1.49, 1.49, 2.49]
}
```

Calling `visualize_table` on `fruit` would produce the following:

```python
>>> visualize_table(fruit)

    fruit  price
0   apple   1.49
1  orange   1.49
2   peach   2.49
```

### bar(table, x, y)

If you want to graph categorical data, you can use the `bar` function; it produces a bar graph given a table, the x-axis column, and the y-axis column. If the following table is `fruit`:

| Fruit    | Price |
| -------- | ----- |
| "apple"  | 1.49  |
| "orange" | 1.49  |
| "peach"  | 2.49  |

Calling the `bar` function would do the following:

```python
>>> fruit = {
    'fruit': 
        ['apple', 'orange', 'peach'], 
    'price': 
        [1.49, 1.49, 2.49]
}
>>> bar(fruit, 'fruit', 'price')
# input 1: the table; input 2: the x-axis column name; 
# input 3: the y-axis column name
```

![](/files/-LkNMqPgTbklp1O2Wcto)

### line(table, x, y)

If you want to graph two different kinds of numerical data against each other, you can use the `line` function; it produces a line graph given a table, the x-axis column, and the y-axis column. If the following table is `population`:

| Year | Population |
| ---- | ---------- |
| 1900 | 123,432    |
| 1905 | 126,743    |
| 1910 | 134,894    |
| 1915 | 156,483    |

Calling the `line` function would do the following:

```python
>>> population = {
    'year': 
        [1900, 1905, 1910, 1915], 
    'population': 
        [123432, 126743, 134894, 156483]
}
>>> line(population, 'year', 'population')
# input 1: the table; input 2: the x-axis column name; 
# input 3: the y-axis column name
```

![](/files/-LkNOR2KCotYw0EdfXKt)