Sketch first exercises day 3 morning

Author: richelbilderbeek

docs/day3/matplotlib/README.md

@@ -29,6 +29,21 @@ Tetralith  |`module load buildtool-easybuild/4.8.0-hpce082752a2 GCC/13.2.0 Pytho
 
 <!-- markdownlint-enable MD013 -->
 
+## Exercises
+
+```python
+import matplotlib as mpl
+import matplotlib.pyplot as plt
+
+x = np.linspace(0, 10, 100)
+
+plt.plot(x, np.sin(x))
+plt.plot(x, np.cos(x))
+
+# plt.show()
+plt.figure().savefig('my_figure.png') # Unsure if this works
+
+```
 
 ## External links
 

docs/day3/pandas/README.md

@@ -28,6 +28,53 @@ Tetralith  |`module load buildtool-easybuild/4.8.0-hpce082752a2 GCC/13.2.0 Pytho
 
 <!-- markdownlint-enable MD013 -->
 
+## Exercises
+
+## Exercise 1: minimal code
+
+Get this code to run:
+
+```python
+import pandas
+print(pandas.__version__)
+```
+
+## Exercise 2
+
+Depends on Matplotlib
+
+Series:
+
+```python
+# 
+data = pd.Series([0.25, 0.5, 0.75, 1.0])
+data = pd.Series({2:'a', 1:'b', 3:'c'})
+print(data.values)
+```
+
+Data frame:
+
+```python
+population_dict = {'California': 38332521,
+                   'Texas': 26448193,
+                   'New York': 19651127,
+                   'Florida': 19552860,
+                   'Illinois': 12882135}
+population = pd.Series(population_dict)
+population
+area_dict = {'California': 423967, 'Texas': 695662, 'New York': 141297,
+             'Florida': 170312, 'Illinois': 149995}
+area = pd.Series(area_dict)
+area
+states = pd.DataFrame({'population': population,
+                       'area': area})
+states
+```
+
+## Done?
+
+Go to [the session about Matplotlib](../matplotlib/README.md)
+
 ## External links
 
 - [Python Data Science Handbook](https://jakevdp.github.io/PythonDataScienceHandbook/)

docs/day3/seaborn/README.md

@@ -29,6 +29,46 @@ Dardel     |`module load cray-python/3.11.7 PDCOLD/23.12 matplotlib/3.8.2-cpeGNU
 
 <!-- markdownlint-enable MD013 -->
 
+## Exercises
+
+```python
+import matplotlib.pyplot as plt
+plt.style.use('classic')
+%matplotlib inline
+import numpy as np
+import pandas as pd
+
+# Create some data
+rng = np.random.RandomState(0)
+x = np.linspace(0, 10, 500)
+y = np.cumsum(rng.randn(500, 6), 0)
+
+# Plot the data with Matplotlib defaults
+plt.plot(x, y)
+plt.legend('ABCDEF', ncol=2, loc='upper left');
+
+
+import seaborn as sns
+sns.set()
+
+
+# same plotting code as above!
+plt.plot(x, y)
+plt.legend('ABCDEF', ncol=2, loc='upper left');
+```
+
+```python
+data = np.random.multivariate_normal([0, 0], [[5, 2], [2, 2]], size=2000)
+data = pd.DataFrame(data, columns=['x', 'y'])
+
+# Two overlaid density plots
+for col in 'xy':
+    sns.kdeplot(data[col], shade=True)
+
+# Density plot
+sns.kdeplot(data);
+```
+
 ## External links
 
 - [Python Data Science Handbook](https://jakevdp.github.io/PythonDataScienceHandbook/)

evaluations/20250425_day_2/README.md

@@ -13,20 +13,20 @@ From the registration form.
 
 Using cluster                           |Number of learners
 ----------------------------------------|------------------
-Using NAISS cluster                     |35 
-Using local university cluster       |13 
-Previously used NAISS/SNIC             |7 
-Previously used local/university cluster|8 
-Other clusters                        |5 
-Never used clusters                 |10 
-     
+Using NAISS cluster                     |35
+Using local university cluster       |13
+Previously used NAISS/SNIC             |7
+Previously used local/university cluster|8
+Other clusters                        |5
+Never used clusters                 |10
+
 Using Python                                                                                     |Number of learners
 -------------------------------------------------------------------------------------------------|------------------
 I have no previous experience with Python                                          |6
 I know Python at a beginner level, can write very simple Python code, can import a Python package|25
 I have an intermediate knowledge of Python. I can install Python packages          |15
 I am proficient in Python                                                          |16
-     
+
 Using Linux                                                                                                                                  |Number of learners
 ---------------------------------------------------------------------------------------------------------------------------------------------|-------------------
 I have never used Linux/Unix                                                                                                  |3

meeting_notes/2022_1_spring.md

@@ -109,6 +109,7 @@
 UPPMAX and HPC2n is organising a joint workshop on how to run Python and install additional Python packages on the computer resources provided by UPPMAX and HPC2N and how to use the HPC capabilities. Participants will be able to bring their particular software request for discussion as well.
 
 **The following will be covered:**
+
 - Loading the appropriate Python module
 - Packages
   - checking installed packages

meeting_notes/2022_2_autumn.md

@@ -132,7 +132,7 @@ Don’t know 25%
 5|13.50 | **Leg stretch**
 20 | 13.55 |ML intro|+demos
 25| 14.15 |UPPMAX session2| Lecture +Ex? | jupyter, Bianca
-25| 14.15|HPC2N session2|Lecture + Ex?|ML exercise|  User interaction |   
+25| 14.15|HPC2N session2|Lecture + Ex?|ML exercise|  User interaction |
 |**15**|14.40 |**Coffee**||
 15| 14.55 |Summary| Lecture|Describe when to do what| Keypoints
 25| 15.10| Exercises not recorded

meeting_notes/2023_1_spring.md

@@ -271,6 +271,7 @@ UPPMAX and HPC2n is organising a joint workshop on how to run Python and install
 The instructors will use UPPMAX's systems for demos and there will be hands-on exercises for the participants.
 
 **The following will be covered:**
+
 - Loading the appropriate Python module
 - Packages
   - checking installed packages

meeting_notes/2023_2_autumn.md

@@ -112,6 +112,7 @@
   - ToDos: See last meeting
 
 ### Meeting 24 Oct 15.15
+
 - Suggestions from Björn
   - minimize packages sections
     - [x] links and keypoints from October course

meeting_notes/2024_1_spring.md

@@ -4,6 +4,7 @@
 * onboarding 14 May at 1.15-2pm
 
 ## Next meeting May 29 13.00
+
 * Evaluation
   * big data
   * point to other on-line material for specific science topics
@@ -17,6 +18,7 @@
       * not learning the solutions of the problems!
 
 ## Next meeting May 8 13:00
+
 * Status
   * number: 57?
   * Rebecca is contacted for fall python/matlab training
@@ -41,6 +43,7 @@
   *
 
 ## Next meeting May 2 10:00
+
 * Status
   * BC
     * just started due to other duties (new web going live tomorrow)
@@ -69,6 +72,7 @@
 * Postponed
 
 ## Next meeting April 10 13.00
+
 * Short one
 * Status
   * what is needed?
@@ -124,10 +128,12 @@ Question session (breakout)| X | X | X
 Summary| X | X | X
 
 ## Meeting 27 March
+
 * HPC Python: May 15th: leave everything the same: Bi + Bj + Pe teach, Ri assists
   * with updates of course from earlier learnings
   * py/3.11 (GPU UPPMAX perhaps other solution)
 
 ### Meeting 15 feb
+
 * ToDos
   * [x] UPPMAX web page

meeting_notes/2024_2_autumn.md

@@ -260,19 +260,19 @@ Next meeting
 
 - Install package at 10
   - Fine!?
-- Batch mode:   
+- Batch mode:
   - Perfect!
 - Interactive on compute node (be clear en session title)
   - Let students try Jupyter in exercise
   - more hands-on
   - NOTE: Look into Spyder
 - Parallel computing  
   - More hands-on
-- GPUs   
+- GPUs
   - Same material but faster?
   - Or Extra material?
   - exercises
-- ML   
+- ML
   - More exercises?
   - NOTE: will extend!