Exercise

# Apply time series decomposition to your dataset

You will now perform time series decomposition on multiple time series. You can achieve this by leveraging the Python `dict`

ionary to store the results of each time series decomposition.

In this exercise, you will initialize an empty dictionary with a set of curly braces, `{}`

, use a `for`

loop to iterate through the columns of the DataFrame and apply time series decomposition to each time series. After each time series decomposition, you place the results in the dictionary by using the command `my_dict[key] = value`

, where `my_dict`

is your dictionary, `key`

is the name of the column/time series, and `value`

is the decomposition object of that time series.

Instructions

**100 XP**

- Initialize an empty dictionary called
`jobs_decomp`

. - Extract the column names of the
`jobs`

DataFrame and place the results in a list called`jobs_names`

. - Iterate through each column in
`jobs_names`

and apply time series decomposition to that time series. Place the results in the`jobs_decomp`

dictionary, where the column name is the key, and the value is the decomposition of the time series you just performed.