From b264f4a39b44d8dd30372e339249dd1171194c97 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Bj=C3=B8rn=20Sand=20Jensen?= <bjje@dtu.dk>
Date: Fri, 26 Jan 2024 19:48:07 +0100
Subject: [PATCH] Print the data file location in ex1.5.1-1.5.3,1.5.5
---
exercises/02450Toolbox_Python/Scripts/ex1_5_1.py | 6 ++++++
exercises/02450Toolbox_Python/Scripts/ex1_5_2.py | 10 +++++++---
exercises/02450Toolbox_Python/Scripts/ex1_5_3.py | 10 ++++++++--
exercises/02450Toolbox_Python/Scripts/ex1_5_5.py | 8 +++++++-
4 files changed, 28 insertions(+), 6 deletions(-)
diff --git a/exercises/02450Toolbox_Python/Scripts/ex1_5_1.py b/exercises/02450Toolbox_Python/Scripts/ex1_5_1.py
index d5c7463..41c5373 100644
--- a/exercises/02450Toolbox_Python/Scripts/ex1_5_1.py
+++ b/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.
diff --git a/exercises/02450Toolbox_Python/Scripts/ex1_5_2.py b/exercises/02450Toolbox_Python/Scripts/ex1_5_2.py
index 7c28d1b..d421597 100644
--- a/exercises/02450Toolbox_Python/Scripts/ex1_5_2.py
+++ b/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
diff --git a/exercises/02450Toolbox_Python/Scripts/ex1_5_3.py b/exercises/02450Toolbox_Python/Scripts/ex1_5_3.py
index 97b9692..cf1fbac 100644
--- a/exercises/02450Toolbox_Python/Scripts/ex1_5_3.py
+++ b/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.
diff --git a/exercises/02450Toolbox_Python/Scripts/ex1_5_5.py b/exercises/02450Toolbox_Python/Scripts/ex1_5_5.py
index e1b6d01..4b761a8 100644
--- a/exercises/02450Toolbox_Python/Scripts/ex1_5_5.py
+++ b/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
--
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