diff --git a/00_python/01_Python_Basics.html b/00_python/01_Python_Basics.html index 2aef289..27e70da 100644 --- a/00_python/01_Python_Basics.html +++ b/00_python/01_Python_Basics.html @@ -445,7 +445,7 @@

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Introduction to Python in Jupyter Notebook/Google Colab#

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1.2.2.3 Using Variablesprint(float1 * float2) print(float1 / float2) -#Here's an interesting one that showed up in the first homework in 2017. Modulus: +#Here's an interesting one that showed up in the first homework in 2017. Modulus: print(5 % 2) @@ -704,10 +704,10 @@

1.2.2.5 Loops in Pythonwhile(i < len(fib)): print(fib[i]) i = i + 1 - + #In matlab, to do the same thing you would have the conditional as: counter < (length(fib) + 1) #This is because matlab starts indexing at 1, and python starts at 0. - + #The above type of loop is so common that the 'for' loop is the way to write it faster. print("Let's try that again") diff --git a/01_pandas_statistics/01_Pandas_Intro.html b/01_pandas_statistics/01_Pandas_Intro.html index 979be0a..e5e890f 100644 --- a/01_pandas_statistics/01_Pandas_Intro.html +++ b/01_pandas_statistics/01_Pandas_Intro.html @@ -425,7 +425,8 @@

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Open in Colab

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Introduction to Pandas#

pandas is a column-oriented data analysis API. It’s a great tool for handling and analyzing input data, and many ML frameworks support pandas data structures as inputs. Although a comprehensive introduction to the pandas API would span many pages, the core concepts are fairly straightforward, and we’ll present them below. For a more complete reference, the pandas docs site contains extensive documentation and many tutorials.

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Exercise
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blobs_df = pd.read_csv('../../data/blobs_statistics.csv')
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blobs_df = pd.read_csv("https://github.com/vmcf-konfmi/MB100T01/raw/main/data/blobs_statistics.csv")
+#blobs_df = pd.read_csv('../../data/blobs_statistics.csv')
 blobs_df
 
diff --git a/01_pandas_statistics/02_Pandas_operations.html b/01_pandas_statistics/02_Pandas_operations.html index a44a468..90399ea 100644 --- a/01_pandas_statistics/02_Pandas_operations.html +++ b/01_pandas_statistics/02_Pandas_operations.html @@ -423,7 +423,8 @@

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Open in Colab

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Basic Operations#

Inspiration and some of the parts came from: Python Data Science GitHub repository, MIT License and Introduction to Pandas by Google, Apache 2.0

If running this from Google Colab, uncomment the cell below and run it. Otherwise, just skip it.

diff --git a/01_pandas_statistics/03_Pandas_EDA.html b/01_pandas_statistics/03_Pandas_EDA.html index 55ad1de..45e2548 100644 --- a/01_pandas_statistics/03_Pandas_EDA.html +++ b/01_pandas_statistics/03_Pandas_EDA.html @@ -416,7 +416,8 @@

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Open in Colab

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Exploratory Data Analysis#

Inspiration and some of the parts came from: Python Data Science GitHub repository, MIT License and Introduction to Pandas by Google, Apache 2.0

If running this from Google Colab, uncomment the cell below and run it. Otherwise, just skip it.

diff --git a/01_pandas_statistics/04_Pandas_Bonus.html b/01_pandas_statistics/04_Pandas_Bonus.html index 1e59ee1..73690b3 100644 --- a/01_pandas_statistics/04_Pandas_Bonus.html +++ b/01_pandas_statistics/04_Pandas_Bonus.html @@ -425,7 +425,8 @@

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Open in Colab

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Basic Plots, Groupping and Multi-Level Tables#

Inspiration and some of the parts came from: Python Data Science GitHub repository, MIT License and Introduction to Pandas by Google, Apache 2.0

If running this from Google Colab, uncomment the cell below and run it. Otherwise, just skip it.

diff --git a/01_pandas_statistics/05_Statistic.html b/01_pandas_statistics/05_Statistic.html index 3f9b5d1..1eeb7b9 100644 --- a/01_pandas_statistics/05_Statistic.html +++ b/01_pandas_statistics/05_Statistic.html @@ -448,7 +448,8 @@

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Open in Colab

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Statistics#

Sources and inspiration: