Added pandas notes

3 files changed, 31 insertions, 3 deletions

diff --git a/tutorials/module_4/1_importing_scientific_data.md b/tutorials/module_4/1_importing_scientific_data.md
index 9cfedbe..94bad93 100644
--- a/tutorials/module_4/1_importing_scientific_data.md
+++ b/tutorials/module_4/1_importing_scientific_data.md
@@ -3,7 +3,7 @@
 [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.
+Pandas is a library that is built on top of NumPy and is therefore customarily to import both when working with Pandas.
 
 ```python
 import numpy as np
diff --git a/tutorials/module_4/Pandas.md b/tutorials/module_4/Pandas.md
index d62ee48..672661f 100644
--- a/tutorials/module_4/Pandas.md
+++ b/tutorials/module_4/Pandas.md
@@ -1,4 +1,26 @@
 Pandas
 Panel Data
 
-https://pandas.pydata.org/docs/getting_started/comparison/comparison_with_spreadsheets.html#compare-with-spreadsheets
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+https://pandas.pydata.org/docs/getting_started/comparison/comparison_with_spreadsheets.html#compare-with-spreadsheets
+
+
+
+
+
+https://pandas.pydata.org/docs/getting_started/intro_tutorials/02_read_write.html
+
+
+
+https://pandas.pydata.org/docs/getting_started/intro_tutorials/03_subset_data.html
+
+https://pandas.pydata.org/docs/getting_started/intro_tutorials/05_add_columns.html
+
+
+https://pandas.pydata.org/docs/user_guide/reshaping.html
+
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+https://pandas.pydata.org/docs/user_guide/merging.html
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+
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+https://pandas.pydata.org/docs/getting_started/intro_tutorials/08_combine_dataframes.html
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diff --git a/tutorials/module_4/data cleaning.md b/tutorials/module_4/data cleaning.md
index efd2889..62b5091 100644
--- a/tutorials/module_4/data cleaning.md
+++ b/tutorials/module_4/data cleaning.md
@@ -78,4 +78,10 @@ Figure 8. MATLAB plots of clean and noisy speech signals and denoised output fro
 
 Microsoft® Excel® is a common tool for cleaning and preparing data. It offers built-in commands, such as Remove Duplicates and Find and Replace, that you can use to standardize data sets. You can also apply conditional formatting to highlight inconsistencies or use [pivot tables](https://www.mathworks.com/help/matlab/ref/pivottable.html) to identify and correct errors. However, for larger data sets, tasks such as handling missing values, merging data sets, or applying custom logic often need to be done manually. Lack of automation can increase the risk of unintended errors and inconsistencies in processing, especially when working with complex data sets.
 
-MATLAB can help with some of the more time-consuming parts of data cleaning in Excel, especially when working with larger data sets. MATLAB scripts and functions make data cleaning transformations transparent, so you can always see what steps are taken and adjust as needed. For example, instead of manually searching for missing values, you can use `fillmissing` to automatically handle gaps in data. By using MATLAB with Excel, you can handle messier data sets more consistently while keeping control over the process.
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+MATLAB can help with some of the more time-consuming parts of data cleaning in Excel, especially when working with larger data sets. MATLAB scripts and functions make data cleaning transformations transparent, so you can always see what steps are taken and adjust as needed. For example, instead of manually searching for missing values, you can use `fillmissing` to automatically handle gaps in data. By using MATLAB with Excel, you can handle messier data sets more consistently while keeping control over the process.
+
+
+---
+https://pandas.pydata.org/docs/getting_started/intro_tutorials/10_text_data.html
+
+https://pandas.pydata.org/docs/user_guide/missing_data.html
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