relocate solutions for episode 04

Author: tobyhodges

episodes/04-data-types-and-format.md

@@ -247,6 +247,37 @@ surveys_df['plot_id'].astype("float")
 Next try converting `weight` to an integer. What goes wrong here? What is pandas telling you?
 We will talk about some solutions to this later.
 
+::::::::::::::::::::::: solution
+
+```python
+surveys_df['plot_id'].astype("float")
+```
+
+```output
+0         2.0
+1         3.0
+2         2.0
+3         7.0
+4         3.0
+         ... 
+35544    15.0
+35545    15.0
+35546    10.0
+35547     7.0
+35548     5.0
+```
+
+```python
+surveys_df['weight'].astype("int")
+```
+
+```error
+pandas.errors.IntCastingNaNError: Cannot convert non-finite values (NA or inf) to integer
+```
+
+Pandas cannot convert types from float to int if the column contains NaN values.
+
+::::::::::::::::::::::::::::::::
 
 ::::::::::::::::::::::::::::::::::::::::::::::::::
 
@@ -348,7 +379,35 @@ Count the number of missing values per column.
 The method `.count()` gives you the number of non-NaN observations per column.
 Try looking to the `.isna()` method.
 
+::::::::::::::::::::::: solution
+
+```python
+for c in surveys_df.columns:
+    print(c, len(surveys_df[surveys_df[c].isna()]))
+```
+
+Or, since we've been using the `pd.isnull` function so far:
+
+```python
+for c in surveys_df.columns:
+    print(c, len(surveys_df[pd.isnull(surveys_df[c])]))
+```
+
+```output
+record_id 0
+month 0
+day 0
+year 0
+plot_id 0
+species_id 763
+sex 2511
+hindfoot_length 4111
+weight 3266
+```
+
+Note that `isnull` and `isna` are equivalent: they behave identically.
 
+::::::::::::::::::::::::::::::::
 
 :::::::::::::::::::::::::
 

instructors/instructor-notes.md

@@ -299,43 +299,6 @@ surveys_df[~surveys_df["sex"].isin(['M', 'F'])]
 
 ## 04-data-types-and-format
 
-### Challenge - Changing Types
-
-- Try converting the column `plot_id` to floats using `surveys_df.plot_id.astype("float")`.
-  Then, try converting the contents of the `weight` column to an integer type.
-  What error messages does Pandas give you? What do these errors mean?
-
-Pandas cannot convert types from float to int if the column contains NaN values.
-
-### Challenge - Counting
-
-- Count the number of missing values per column. Hint: The method `.count()` gives you the number of
-  non-NA observations per column. Try looking to the `.isnull()` method.
-
-```python
-for c in surveys_df.columns:
-    print(c, len(surveys_df[surveys_df[c].isnull()]))
-```
-
-Or, since we've been using the `pd.isnull` function so far:
-
-```python
-for c in surveys_df.columns:
-    print(c, len(surveys_df[pd.isnull(surveys_df[c])]))
-```
-
-```output
-record_id 0
-month 0
-day 0
-year 0
-plot_id 0
-species_id 763
-sex 2511
-hindfoot_length 4111
-weight 3266
-```
-
 ### Writing Out Data to CSV
 
 If the students have trouble generating the output, or anything happens with that, the folder