Print the data file location in ex1.5.1-1.5.3,1.5.5

exercises/02450Toolbox_Python/Scripts/ex1_5_1.py

@@ -5,6 +5,12 @@ import pandas as pd
 
 # Load the Iris csv data using the Pandas library
 filename = importlib_resources.files("dtuimldmtools").joinpath("data/iris.csv")
+
+# Print the location of the iris.csv file on your computer. 
+# You should inspect it manually to understand the format and content
+print("\nLocation of the iris.csv file: {}".format(filename))
+
+# Load the iris.csv file using pandas
 df = pd.read_csv(filename)
 
 # Pandas returns a dataframe, (df) which could be used for handling the data.

exercises/02450Toolbox_Python/Scripts/ex1_5_2.py

@@ -11,11 +11,15 @@ import xlrd
 # data to excel files, see the following tutorial:
 # http://www.simplistix.co.uk/presentations/python-excel.pdf}
 
-# Load xls sheet with data
-# There's only a single sheet in the .xls, so we take out that sheet
-
+# Get path to the datafile
 filename = importlib_resources.files("dtuimldmtools").joinpath("data/iris.xls")
 
+# Print the location of the iris.xls file on your computer. 
+# You should inspect it manually to understand the format and content
+print("\nLocation of the iris.xls file: {}".format(filename))
+
+# Load xls sheet with data
+# There's only a single sheet in the .xls, so we take out that sheet
 doc = xlrd.open_workbook(filename).sheet_by_index(0)
 
 # Extract attribute names

exercises/02450Toolbox_Python/Scripts/ex1_5_3.py

@@ -7,10 +7,16 @@ from scipy.io import loadmat
 # The matlab workspace is loaded as a dictionary, with keys corresponding to
 # matlab variable names, and values to arrays representing matlab matrices.
 
-# Load Matlab data file to python dict structure
-
+# Get path to the datafile
 filename = importlib_resources.files("dtuimldmtools").joinpath("data/iris.mat")
+
+# Print the location of the iris.mat file on your computer. 
+# You should inspect it manually to understand the format and content
+print("\nLocation of the iris.mat file: {}".format(filename))
+
+# Load Matlab data file to python dict structure
 iris_mat = loadmat(filename, squeeze_me=True)
+
 # The argument squeeze_me ensures that there the variables we get from the
 # MATLAB filed are not stored within "unneeded" array dimensions.
 

exercises/02450Toolbox_Python/Scripts/ex1_5_5.py

@@ -9,7 +9,13 @@ import pandas as pd
 # We start by defining the path to the file that we're we need to load.
 # Upon inspection, we saw that the messy_data.data was infact a file in the
 # format of a CSV-file with a ".data" extention instead.
-filename = importlib_resources.files("dtuimldmtools").joinpath("data/messy_data/messy_data.data")
+foldername = importlib_resources.files("dtuimldmtools").joinpath("data/messy_data")
+filename = foldername.joinpath("messy_data.data")
+
+# Print the location of the messy_data folder and file. 
+# You should inspect it manually to understand the format and content
+print("\nLocation of the messy_data folder: {}".format(foldername))
+print("\nLocation of the messy_data.data file: {}\n".format(filename))
 
 # First of we simply read the file in using readtable, however, we need to
 # tell the function that the file is tab-seperated. We also need to specify