added further solutions

Author: beyondsimulations

part-08/solution/lecture_numpy1.py

@@ -0,0 +1,6 @@
+# TODO: Create an array with 10 evenly spaced numbers over the interval from 0 to 73.
+
+import numpy as np
+# YOUR CODE HERE
+
+print(np.linspace(0, 73, 10))

part-08/solution/lecture_numpy2.py

@@ -0,0 +1,6 @@
+# TODO: Take the following 3x3 array and reduce it to a 1D array.
+
+import numpy as np
+array = np.array([[1, 2, 3], [4, 5, 6], [7, 8, 9]])
+# YOUR CODE HERE
+print(array.flatten())

part-08/solution/lecture_pandas_filter.py

@@ -7,7 +7,7 @@
 
 df = pd.read_csv("part-08/data/employees.csv")
 
-df = df[df["Position"] != "Manager"]
+#df = df[df["Position"] == "Manager"]
 
 print("Filtered DataFrame:")
 print(df.head())
@@ -17,5 +17,5 @@
 
 df = df[df["Salary"] == df["Salary"].min()]
 
-print("Highest paid employee:")
+print("Minimal paid employee:")
 print(df["Name"])