solutions and writing good

nickeubank · Oct 3, 2023 · a7a803d · a7a803d
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diff --git a/docs/html/.doctrees/autograder_guidelines.doctree b/docs/html/.doctrees/autograder_guidelines.doctree
diff --git a/docs/html/.doctrees/environment.pickle b/docs/html/.doctrees/environment.pickle
diff --git a/docs/html/.doctrees/exercises/Exercise_dask.doctree b/docs/html/.doctrees/exercises/Exercise_dask.doctree
diff --git a/docs/html/.doctrees/nbsphinx/autograder_guidelines.ipynb b/docs/html/.doctrees/nbsphinx/autograder_guidelines.ipynb
@@ -11,7 +11,7 @@
     "\n",
     "The autograder will expect you to upload a Jupyter Notebook with Python code. The notebook will then be executed, and then the autograder will look for a dictionary called `results` in which it expects you to have stored your answers. The autograder will expect your answers to be stored using the strings specified in the exercise as keys (e.g. you may be asked to store the youngest age in a dataset with the key `\"ex5_age_young\"`).\n",
     "\n",
-    "However, be aware TAs will _also_ review your notebooks for answers to other questions and to ensure your notebook is well written and formatted, so even though the *autograder* won't care if you organize your notebook well and explain what you're doing clearly, we will! So please use [best practices in writing good notebooks.](writing_good_jupyter_notebooks.ipynb)\n",
+    "However, be aware TAs will _also_ review your notebooks for answers to other questions and to ensure your notebook is well written and formatted, so even though the *autograder* won't care if you organize your notebook well and explain what you're doing clearly, we will! So please use [best practices in writing good notebooks.](https://nickeubank.github.io/practicaldatascience_book/notebooks/PDS_not_yet_in_coursera/20_programming_concepts/writing_good_jupyter_notebooks.html)\n",
     "\n",
     "When storing numeric answers, please put the exact computed value into your `results` dictionary. We will use `np.isclose()` to evaluate numeric solutions to be sure that very small floating point errors won't cause problems, but the closer you are to an exact solution the less likely you are to have issues.\n"
    ]

diff --git a/docs/html/.doctrees/nbsphinx/solutions.ipynb b/docs/html/.doctrees/nbsphinx/solutions.ipynb
@@ -12,7 +12,8 @@
    "metadata": {},
    "source": [
     "- [Numpy Vector Solutions](exercises/Solutions_numpy_vectors.ipynb)\n",
-    "- [Pandas Series](exercises/Solutions_series.ipynb)\n"
+    "- [Pandas Series](exercises/Solutions_series.ipynb)\n",
+    "- [Pandas DataFrames](exercises/Solutions_dataframe.ipynb)\n"
    ]
   }
  ],

diff --git a/docs/html/.doctrees/solutions.doctree b/docs/html/.doctrees/solutions.doctree
diff --git a/docs/html/_sources/autograder_guidelines.ipynb.txt b/docs/html/_sources/autograder_guidelines.ipynb.txt
@@ -11,7 +11,7 @@
                 "\n",
                 "The autograder will expect you to upload a Jupyter Notebook with Python code. The notebook will then be executed, and then the autograder will look for a dictionary called `results` in which it expects you to have stored your answers. The autograder will expect your answers to be stored using the strings specified in the exercise as keys (e.g. you may be asked to store the youngest age in a dataset with the key `\"ex5_age_young\"`).\n",
                 "\n",
-                "However, be aware TAs will _also_ review your notebooks for answers to other questions and to ensure your notebook is well written and formatted, so even though the *autograder* won't care if you organize your notebook well and explain what you're doing clearly, we will! So please use [best practices in writing good notebooks.](writing_good_jupyter_notebooks.ipynb)\n",
+                "However, be aware TAs will _also_ review your notebooks for answers to other questions and to ensure your notebook is well written and formatted, so even though the *autograder* won't care if you organize your notebook well and explain what you're doing clearly, we will! So please use [best practices in writing good notebooks.](https://nickeubank.github.io/practicaldatascience_book/notebooks/PDS_not_yet_in_coursera/20_programming_concepts/writing_good_jupyter_notebooks.html)\n",
                 "\n",
                 "When storing numeric answers, please put the exact computed value into your `results` dictionary. We will use `np.isclose()` to evaluate numeric solutions to be sure that very small floating point errors won't cause problems, but the closer you are to an exact solution the less likely you are to have issues.\n"
             ]

diff --git a/docs/html/_sources/solutions.ipynb.txt b/docs/html/_sources/solutions.ipynb.txt
@@ -12,7 +12,8 @@
    "metadata": {},
    "source": [
     "- [Numpy Vector Solutions](exercises/Solutions_numpy_vectors.ipynb)\n",
-    "- [Pandas Series](exercises/Solutions_series.ipynb)\n"
+    "- [Pandas Series](exercises/Solutions_series.ipynb)\n",
+    "- [Pandas DataFrames](exercises/Solutions_dataframe.ipynb)\n"
    ]
   }
  ],

diff --git a/docs/html/autograder_guidelines.html b/docs/html/autograder_guidelines.html
diff --git a/docs/html/autograder_guidelines.ipynb b/docs/html/autograder_guidelines.ipynb
@@ -11,7 +11,7 @@
     "\n",
     "The autograder will expect you to upload a Jupyter Notebook with Python code. The notebook will then be executed, and then the autograder will look for a dictionary called `results` in which it expects you to have stored your answers. The autograder will expect your answers to be stored using the strings specified in the exercise as keys (e.g. you may be asked to store the youngest age in a dataset with the key `\"ex5_age_young\"`).\n",
     "\n",
-    "However, be aware TAs will _also_ review your notebooks for answers to other questions and to ensure your notebook is well written and formatted, so even though the *autograder* won't care if you organize your notebook well and explain what you're doing clearly, we will! So please use [best practices in writing good notebooks.](writing_good_jupyter_notebooks.ipynb)\n",
+    "However, be aware TAs will _also_ review your notebooks for answers to other questions and to ensure your notebook is well written and formatted, so even though the *autograder* won't care if you organize your notebook well and explain what you're doing clearly, we will! So please use [best practices in writing good notebooks.](https://nickeubank.github.io/practicaldatascience_book/notebooks/PDS_not_yet_in_coursera/20_programming_concepts/writing_good_jupyter_notebooks.html)\n",
     "\n",
     "When storing numeric answers, please put the exact computed value into your `results` dictionary. We will use `np.isclose()` to evaluate numeric solutions to be sure that very small floating point errors won't cause problems, but the closer you are to an exact solution the less likely you are to have issues.\n"
    ]

diff --git a/docs/html/searchindex.js b/docs/html/searchindex.js
diff --git a/docs/html/solutions.html b/docs/html/solutions.html
diff --git a/docs/html/solutions.ipynb b/docs/html/solutions.ipynb
@@ -12,7 +12,8 @@
    "metadata": {},
    "source": [
     "- [Numpy Vector Solutions](exercises/Solutions_numpy_vectors.ipynb)\n",
-    "- [Pandas Series](exercises/Solutions_series.ipynb)\n"
+    "- [Pandas Series](exercises/Solutions_series.ipynb)\n",
+    "- [Pandas DataFrames](exercises/Solutions_dataframe.ipynb)\n"
    ]
   }
  ],

diff --git a/source/autograder_guidelines.ipynb b/source/autograder_guidelines.ipynb
@@ -11,7 +11,7 @@
                 "\n",
                 "The autograder will expect you to upload a Jupyter Notebook with Python code. The notebook will then be executed, and then the autograder will look for a dictionary called `results` in which it expects you to have stored your answers. The autograder will expect your answers to be stored using the strings specified in the exercise as keys (e.g. you may be asked to store the youngest age in a dataset with the key `\"ex5_age_young\"`).\n",
                 "\n",
-                "However, be aware TAs will _also_ review your notebooks for answers to other questions and to ensure your notebook is well written and formatted, so even though the *autograder* won't care if you organize your notebook well and explain what you're doing clearly, we will! So please use [best practices in writing good notebooks.](writing_good_jupyter_notebooks.ipynb)\n",
+                "However, be aware TAs will _also_ review your notebooks for answers to other questions and to ensure your notebook is well written and formatted, so even though the *autograder* won't care if you organize your notebook well and explain what you're doing clearly, we will! So please use [best practices in writing good notebooks.](https://nickeubank.github.io/practicaldatascience_book/notebooks/PDS_not_yet_in_coursera/20_programming_concepts/writing_good_jupyter_notebooks.html)\n",
                 "\n",
                 "When storing numeric answers, please put the exact computed value into your `results` dictionary. We will use `np.isclose()` to evaluate numeric solutions to be sure that very small floating point errors won't cause problems, but the closer you are to an exact solution the less likely you are to have issues.\n"
             ]

diff --git a/source/solutions.ipynb b/source/solutions.ipynb
@@ -12,7 +12,8 @@
    "metadata": {},
    "source": [
     "- [Numpy Vector Solutions](exercises/Solutions_numpy_vectors.ipynb)\n",
-    "- [Pandas Series](exercises/Solutions_series.ipynb)\n"
+    "- [Pandas Series](exercises/Solutions_series.ipynb)\n",
+    "- [Pandas DataFrames](exercises/Solutions_dataframe.ipynb)\n"
    ]
   }
  ],