Skip to content

Update 100_Numpy_exercises_with_hints.md #137

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Open
wants to merge 1 commit into
base: master
Choose a base branch
from
Open

Update 100_Numpy_exercises_with_hints.md #137

Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
4 changes: 2 additions & 2 deletions 100_Numpy_exercises_with_hints.md
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -15,7 +15,7 @@ File automatically generated. See the documentation to update questions/answers/
#### 1. Import the numpy package under the name `np` (★☆☆)
`hint: import … as`
#### 2. Print the numpy version and the configuration (★☆☆)
`hint: np.__version__, np.show_config)`
`hint: np.__version__, np.show_config())`
#### 3. Create a null vector of size 10 (★☆☆)
`hint: np.zeros`
#### 4. How to find the memory size of any array (★☆☆)
Expand Down Expand Up @@ -247,4 +247,4 @@ np.sqrt(-1) == np.emath.sqrt(-1)
#### 99. Given an integer n and a 2D array X, select from X the rows which can be interpreted as draws from a multinomial distribution with n degrees, i.e., the rows which only contain integers and which sum to n. (★★★)
`hint: np.logical_and.reduce, np.mod`
#### 100. Compute bootstrapped 95% confidence intervals for the mean of a 1D array X (i.e., resample the elements of an array with replacement N times, compute the mean of each sample, and then compute percentiles over the means). (★★★)
`hint: np.percentile`
`hint: np.percentile`