calculate quartil python 1

calculate quartil python

>>> np.percentile(df.time_diff, 25)  # Q1
0.48333300000000001

>>> np.percentile(df.time_diff, 50)  # median
0.5

>>> np.percentile(df.time_diff, 75)  # Q3
0.51666699999999999

Here is what the above code is Doing:
1. We’re using the `.groupby()` method to group the dataframe by the `user_id` column.
2. We’re using the `.diff()` method to calculate the difference between each row and the previous row.
3. We’re using the `.dropna()` method to drop the first row of each group, which is `NaN` because there is no previous row.
4. We’re using the `.reset_index()` method to reset the index of the dataframe.
5. We’re using the `.rename()` method to rename the `time_diff` column to `time_diff_seconds`.

Now that we have the time difference between each row, we can calculate the average time difference for each user.

**Exercise**

calculate quartil python 2

– Use the `.groupby()` method to group the dataframe by the `user_id` column.
– Use the `.mean()` method to calculate the mean of the `time_diff_seconds` column.
– Assign the result to `average_time_diff`.

**Exercise**

calculate quartil python 2

– Use the `.groupby()` method to group the dataframe by the `user_id` column.
– Use the `.agg()` method to calculate the mean of the `time_diff_seconds` column and the standard deviation of the `time_diff_seconds` column.
– Assign the result to `average_time_diff_and_std`.

**Exercise**

calculate quartil python 2

– Use the `.groupby()` method to group the dataframe by the `user_id` column.
– Use the `.agg()` method to calculate the mean of the `time_diff_seconds` column and the standard deviation of the `time_diff_seconds` column.
– Use the `.reset_index()` method to reset the index of the dataframe.
– Assign the result to `average_time_diff_and_std_reset_index`.

**Exercise**

calculate quartil python 2

– Use the `.groupby()` method to group the dataframe by the `user_id` column.
– Use the `.agg()` method to calculate the mean of the `time_diff_seconds` column and the standard deviation of the `time_diff_seconds` column.
– Use the `.reset_index()` method to reset the index of the dataframe.
– Use the `.rename()` method to rename the `time_diff_seconds_mean` column to `mean_time_diff_seconds` and the `time_diff

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