04.02.numpy-indexing-and-selection-exercises.ipynb

{"nbformat":4,"nbformat_minor":0,"metadata":{"kernelspec":{"display_name":"Python 3","language":"python","name":"python3"},"language_info":{"codemirror_mode":{"name":"ipython","version":3},"file_extension":".py","mimetype":"text/x-python","name":"python","nbconvert_exporter":"python","pygments_lexer":"ipython3","version":"3.6.5"},"colab":{"name":"04.02.numpy-indexing-and-selection-exercises.ipynb","provenance":[],"collapsed_sections":[]}},"cells":[{"cell_type":"markdown","metadata":{"id":"aD1pmHRhy-jn","colab_type":"text"},"source":["# NumPy Indexing and Selection Exercises"]},{"cell_type":"markdown","metadata":{"id":"NqT4zl1HzFWP","colab_type":"text"},"source":["### Import `numpy` using the alias `np`"]},{"cell_type":"code","metadata":{"id":"0D6MDJ_dy-jr","colab_type":"code","colab":{}},"source":[""],"execution_count":0,"outputs":[]},{"cell_type":"markdown","metadata":{"id":"8zQONAMFy-jv","colab_type":"text"},"source":["### We will be using the array `arr` for ALL exercises in this notebook\n","> Run the cell below to instantiate `arr` AND see what it looks like."]},{"cell_type":"code","metadata":{"id":"tJRjuVHpy-jw","colab_type":"code","outputId":"08953f73-274b-4b16-9b82-a30cfd7da5aa","executionInfo":{"status":"ok","timestamp":1577642708020,"user_tz":480,"elapsed":358,"user":{"displayName":"Matt Hess","photoUrl":"","userId":"00800340733434721825"}},"colab":{"base_uri":"https://localhost:8080/","height":69}},"source":["arr = np.arange(1,51)\n","print(arr)"],"execution_count":0,"outputs":[{"output_type":"stream","text":["[ 1  2  3  4  5  6  7  8  9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24\n"," 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48\n"," 49 50]\n"],"name":"stdout"}]},{"cell_type":"markdown","metadata":{"id":"85K6WFuey-j0","colab_type":"text"},"source":["<hr>\n","<br>\n","<br>\n","<br>"]},{"cell_type":"markdown","metadata":{"id":"6K4tagN0y-j1","colab_type":"text"},"source":["# Indexing"]},{"cell_type":"markdown","metadata":{"id":"IGMLC6_By-j2","colab_type":"text"},"source":["### 1. Use Indexing to grab the value `25` from `arr` and store it in variable `avg_age`"]},{"cell_type":"code","metadata":{"id":"5DL1vEyTy-j3","colab_type":"code","colab":{}},"source":[""],"execution_count":0,"outputs":[]},{"cell_type":"markdown","metadata":{"id":"m3tNxfvLy-j6","colab_type":"text"},"source":["#### Check your work."]},{"cell_type":"markdown","metadata":{"id":"ZjU4W8zEy-j6","colab_type":"text"},"source":["The next cell uses the built-in python `assert` statement to ensure that your variable `avg_age` equals the appropriate value. If after running cell, you get an `AssertionError`, then your `avg_age` variable does not contain the appropriate value. If nothing happens after running, then all is good. "]},{"cell_type":"code","metadata":{"id":"YmfpIZD_y-j7","colab_type":"code","colab":{}},"source":["assert avg_age == 25"],"execution_count":0,"outputs":[]},{"cell_type":"markdown","metadata":{"id":"qmhGpkUoy-j-","colab_type":"text"},"source":["<hr>\n","<br>\n","<br>\n","<br>"]},{"cell_type":"markdown","metadata":{"id":"GoooJI7zy-j_","colab_type":"text"},"source":["### 2. Grab the values `13,14,15,16,17,18,19` from `arr` and store them in the variable `teenagers`"]},{"cell_type":"code","metadata":{"id":"-4UeF_5dy-kA","colab_type":"code","colab":{}},"source":[""],"execution_count":0,"outputs":[]},{"cell_type":"markdown","metadata":{"id":"0HXmQzx-y-kD","colab_type":"text"},"source":["#### Check your work."]},{"cell_type":"markdown","metadata":{"id":"DHaDvtJ2y-kD","colab_type":"text"},"source":["The next cell may look funky but its just a built-in numpy function equivalent to the python `assert` check from the previous exercise. If you get an `AssertionError` then your `teenagers` array does not match the desired output."]},{"cell_type":"code","metadata":{"id":"f_OSWmUTy-kE","colab_type":"code","colab":{}},"source":["np.testing.assert_array_equal(teenagers, np.array([13,14,15,16,17,18,19]))"],"execution_count":0,"outputs":[]},{"cell_type":"markdown","metadata":{"id":"UyrZgrA7y-kG","colab_type":"text"},"source":["<hr>\n","<br>\n","<br>"]},{"cell_type":"markdown","metadata":{"id":"QrIMxAoay-kH","colab_type":"text"},"source":["# Boolean Selection"]},{"cell_type":"markdown","metadata":{"id":"U2_g-QNIy-kI","colab_type":"text"},"source":["### 3. `Print` sub-array of only those numbers in `arr` *greater than* 21"]},{"cell_type":"code","metadata":{"id":"JpePzfN4y-kI","colab_type":"code","colab":{}},"source":[""],"execution_count":0,"outputs":[]},{"cell_type":"markdown","metadata":{"id":"wECZY03py-kK","colab_type":"text"},"source":["#### Check your work."]},{"cell_type":"markdown","metadata":{"id":"AfDmYdR-y-kL","colab_type":"text"},"source":["The next cell may look funky but its just a built-in numpy function equivalent to the python `assert` check from previous exercises. If you get an `AssertionError` then your `millenials` array does not match the desired output."]},{"cell_type":"code","metadata":{"id":"UWi9-2Icy-kM","colab_type":"code","colab":{}},"source":["np.testing.assert_array_equal(g_thn_21, np.array([22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34,\n","       35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50]))"],"execution_count":0,"outputs":[]},{"cell_type":"markdown","metadata":{"id":"B8_rfqHwy-kO","colab_type":"text"},"source":["<hr>\n","<br>\n","<br>\n","<br>"]},{"cell_type":"markdown","metadata":{"id":"0yEBCWnOy-kO","colab_type":"text"},"source":["# Boolean Selection - Complex"]},{"cell_type":"markdown","metadata":{"id":"k4XFGmY_y-kP","colab_type":"text"},"source":["### 4. Grab a sub-array of only those numbers in `arr` *less than or equal to* `42` **and** greater than or equal to `24` and store in variable `millenials`"]},{"cell_type":"markdown","metadata":{"id":"6BRZmCziy-kP","colab_type":"text"},"source":["> **Hint:** You will need to use the `&` operator between both of the boolean checks to get the appropriate selection array, you can call this array `is_millenial`, if you wish.\n","\n","**For two (or more) conditions, use the `|` and `&` operators, and make sure to use `()` parentheses to seperate each condition.**\n","Example:\n","```python \n","# condition_one and condition_two\n","((condition_one) & (condition_two)) \n","\n","# condition_one or condition_two\n","((condition_one) | (condition_two)) \n","```\n","\n","Create a boolean mask\n","\n","\n"]},{"cell_type":"code","metadata":{"id":"jw4GdphKy-kR","colab_type":"code","colab":{}},"source":[""],"execution_count":0,"outputs":[]},{"cell_type":"markdown","metadata":{"id":"jXVermTM4oHB","colab_type":"text"},"source":["Then, use this selection array to index arr and create millenials"]},{"cell_type":"code","metadata":{"id":"sjWe7HjW4ptW","colab_type":"code","colab":{}},"source":[""],"execution_count":0,"outputs":[]},{"cell_type":"markdown","metadata":{"id":"ivu_14r8y-kW","colab_type":"text"},"source":["#### Check your work."]},{"cell_type":"markdown","metadata":{"id":"xOoG8QvWy-kX","colab_type":"text"},"source":["The next cell may look funky but its just a built-in numpy function equivalent to the python `assert` check from previous exercises. If you get an `AssertionError` then your `millenials` array does not match the desired output."]},{"cell_type":"code","metadata":{"id":"BG1ncY8iy-kY","colab_type":"code","colab":{}},"source":["np.testing.assert_array_equal(millenials, np.array([24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40,\n","       41, 42]))"],"execution_count":0,"outputs":[]}]}