From 29870f542da6f1ec4dd028a4255143b638f48ba8 Mon Sep 17 00:00:00 2001
From: Christian Kolset <christian.kolset@gmail.com>
Date: Fri, 29 Aug 2025 12:41:42 -0600
Subject: Updated canvas to actually refer to the notes in the vault.

This results in the label creation at the top header to reference when showing the block.
---
 tutorials/module_4/1_importing_scientific_data.md | 40 +++++++++++++++++++++++
 tutorials/module_4/2_data_processing.md           | 17 ++++++++++
 tutorials/module_4/3_linear_regression.md         | 24 ++++++++++++++
 tutorials/module_4/data_processing.md             |  1 -
 tutorials/module_4/data_visualization.md          |  3 ++
 tutorials/module_4/importing_scientific_data.md   |  1 -
 tutorials/module_4/linear_regression.md           | 18 ----------
 tutorials/module_4/plotting.md                    |  2 ++
 8 files changed, 86 insertions(+), 20 deletions(-)
 create mode 100644 tutorials/module_4/1_importing_scientific_data.md
 create mode 100644 tutorials/module_4/2_data_processing.md
 create mode 100644 tutorials/module_4/3_linear_regression.md
 delete mode 100644 tutorials/module_4/data_processing.md
 delete mode 100644 tutorials/module_4/importing_scientific_data.md
 delete mode 100644 tutorials/module_4/linear_regression.md

(limited to 'tutorials/module_4')

diff --git a/tutorials/module_4/1_importing_scientific_data.md b/tutorials/module_4/1_importing_scientific_data.md
new file mode 100644
index 0000000..b51558b
--- /dev/null
+++ b/tutorials/module_4/1_importing_scientific_data.md
@@ -0,0 +1,40 @@
+# Importing Scientific Data using Pandas
+
+^8eb966
+
+[Introduction text]
+
+
+Pandas is a library that is built on top of NumPy and is there for customarily to import both when working with Pandas.
+
+```python
+import numpy as np
+import pandas as pd
+```
+
+
+DataFrame
+
+A `DataFrame` in pandas is a two-dimensional data structure like table with rows and columns.
+
+
+
+```python
+# Tensile test data
+data = {
+    "Force (N)": [10, 15, 20, 25],
+    "Displacement (mm)": [1.2, 1.8, 2.5, 3.0],
+    "Stress (MPa)": [2.6, 3.9, 5.2, 6.5],
+}
+```
+
+
+
+Object Creation
+
+```python
+# Create DataFrame with row labels
+df = pd.DataFrame(data, index=["Test1", "Test2", "Test3", "Test4"])
+
+print(df)
+```
\ No newline at end of file
diff --git a/tutorials/module_4/2_data_processing.md b/tutorials/module_4/2_data_processing.md
new file mode 100644
index 0000000..f969b2d
--- /dev/null
+++ b/tutorials/module_4/2_data_processing.md
@@ -0,0 +1,17 @@
+# Data Processing
+
+^7b1480
+
+
+## Data Cleaning and Filtering
+
+
+
+
+
+
+
+---
+## Reading & Writing Files
+
+
diff --git a/tutorials/module_4/3_linear_regression.md b/tutorials/module_4/3_linear_regression.md
new file mode 100644
index 0000000..298d411
--- /dev/null
+++ b/tutorials/module_4/3_linear_regression.md
@@ -0,0 +1,24 @@
+# Linear Regression
+
+^aab594
+
+
+
+## Statical tools
+Numpy comes with some useful statistical tools that we can use to analyze our data.
+
+### Mean
+The mean is the average of a set of numbers. It is calculated by summing all the numbers and dividing by the count of numbers.
+
+```python
+import numpy as np
+
+mean = np.mean([1, 2, 3, 4, 5])
+median = np.median([1, 2, 3, 4, 5])
+std = np.std([1, 2, 3, 4, 5])
+variance = np.var([1, 2, 3, 4, 5])
+```
+
+
+
+###
diff --git a/tutorials/module_4/data_processing.md b/tutorials/module_4/data_processing.md
deleted file mode 100644
index 0f2795e..0000000
--- a/tutorials/module_4/data_processing.md
+++ /dev/null
@@ -1 +0,0 @@
-# Data Processing
diff --git a/tutorials/module_4/data_visualization.md b/tutorials/module_4/data_visualization.md
index 43b0170..fc02427 100644
--- a/tutorials/module_4/data_visualization.md
+++ b/tutorials/module_4/data_visualization.md
@@ -1 +1,4 @@
 # Data Visualization
+
+^1ac244
+
diff --git a/tutorials/module_4/importing_scientific_data.md b/tutorials/module_4/importing_scientific_data.md
deleted file mode 100644
index 5f3e48a..0000000
--- a/tutorials/module_4/importing_scientific_data.md
+++ /dev/null
@@ -1 +0,0 @@
-# Importing Scientific Data
\ No newline at end of file
diff --git a/tutorials/module_4/linear_regression.md b/tutorials/module_4/linear_regression.md
deleted file mode 100644
index b21415b..0000000
--- a/tutorials/module_4/linear_regression.md
+++ /dev/null
@@ -1,18 +0,0 @@
-# Linear Regression
-
-
-
-## Statical tools
-Numpy comes with some useful statistical tools that we can use to analyze our data.
-
-### Mean
-The mean is the average of a set of numbers. It is calculated by summing all the numbers and dividing by the count of numbers.
-
-```python
-import numpy as np
-
-mean = np.mean([1, 2, 3, 4, 5])
-median = np.median([1, 2, 3, 4, 5])
-std = np.std([1, 2, 3, 4, 5])
-variance = np.var([1, 2, 3, 4, 5])
-```
diff --git a/tutorials/module_4/plotting.md b/tutorials/module_4/plotting.md
index 42f82cc..43bea2e 100644
--- a/tutorials/module_4/plotting.md
+++ b/tutorials/module_4/plotting.md
@@ -1,4 +1,6 @@
 # Plotting
 
+^c3a51d
+
 ## matlibplot
 
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