post-TR1 Update attempt 1

Author: eyrei123

how-to-drop-null-values-in-pandas/drop_a_subset.py

@@ -1,5 +1,8 @@
 import pandas as pd
 
+
+pd.set_option("display.max_columns", None)
+
 sales_data = pd.read_csv(
     "sales_data_with_missing_values.csv",
     parse_dates=["order_date"],

how-to-drop-null-values-in-pandas/drop_null_columns.py

@@ -1,5 +1,6 @@
 import pandas as pd
 
+
 sales_data = pd.read_csv(
     "sales_data_with_missing_values.csv",
     parse_dates=["order_date"],

how-to-drop-null-values-in-pandas/drop_null_rows.py

@@ -1,5 +1,7 @@
 import pandas as pd
 
+pd.set_option("display.max_columns", None)
+
 sales_data = pd.read_csv(
     "sales_data_with_missing_values.csv",
     parse_dates=["order_date"],

how-to-drop-null-values-in-pandas/exercise solutions.py renamed to how-to-drop-null-values-in-pandas/exercise_solutions.py

@@ -1,10 +1,8 @@
-import pandas as pd
-
 grades = pd.read_csv(
     "grades.csv",
 ).convert_dtypes(dtype_backend="pyarrow")
 
-# 1. Permanently drop the last row of the dataframe.
+# 1. Use `.dropna()` in such a way that it permanently drops the row in the dataframe containing only null values.
 
 grades.dropna(how="all", inplace=True)
 
@@ -16,10 +14,10 @@
 
 grades.dropna(axis=1)
 
-# 4. Display the exams students have sat five or more times.
+# 4. Display the exams sat by at least five students.
 
-grades.dropna(axis=0, thresh=6)  # Remember there are seven columns.
+grades.dropna(axis=0, thresh=6) # Remember there are seven columns.
 
-# 5. Who else would be in the exam hall when both `S2` and `S4` were there?
+# 5. Who else was in in every exam that both S2 and S4 sat?
 
 grades.dropna(subset=["S2", "S4"]).dropna(axis=1, ignore_index=True)