Python - Cumulative Mean of Dictionary keys

Python - Cumulative Mean of Dictionary keys

To compute the cumulative mean of dictionary keys, we need to take the following steps:

  1. Extract dictionary keys.
  2. Calculate the cumulative mean for the sequence of keys.
  3. Return the list of cumulative means.

Let's illustrate this with an example:

Given a dictionary:

data = { 10: "value1", 20: "value2", 30: "value3", 40: "value4" }

The cumulative mean for the keys would be:

[10, 15, 20, 25]

Let's implement this:

Python: Cumulative Mean of Dictionary keys

def cumulative_mean_keys(data): keys = list(data.keys()) cum_sum = 0 cum_means = [] for i, key in enumerate(keys): cum_sum += key cum_means.append(cum_sum / (i + 1)) return cum_means data = { 10: "value1", 20: "value2", 30: "value3", 40: "value4" } print(cumulative_mean_keys(data)) # Outputs: [10.0, 15.0, 20.0, 25.0]

Explanation:

  1. Extract the keys from the dictionary and convert them to a list.
  2. Iterate over the keys using enumeration to get both the index (i) and the key value (key).
  3. At each step, add the key value to cum_sum.
  4. Compute the mean up to the current key by dividing the cum_sum by i + 1 (because indexing starts from 0).
  5. Append the mean to the cum_means list.
  6. Return the list of cumulative means after the loop.

By using this approach, you can compute the cumulative mean for dictionary keys, which can be useful in various data analysis tasks.

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