baseline interacting with python notebook

Author: mariogiampieri

Tutorials/00_Python_Basics.ipynb

@@ -0,0 +1,120 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "4f27cd01",
+   "metadata": {},
+   "source": [
+    "# Manipulating data"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "64b13fce",
+   "metadata": {},
+   "source": [
+    "Common data structures in Python include:\n",
+    "- list\n",
+    "- object\n",
+    "- dataframe\n",
+    "- series\n",
+    "\n",
+    "Means of manipulating data include:\n",
+    "- indexing\n",
+    "- slicing\n",
+    "- filtering\n",
+    "- sorting\n",
+    "# Indexing\n",
+    "# Indexing is used to access individual elements in a data structure.\n",
+    "# For example, in a list, you can access the first element using an index of 0.\n",
+    "# In a dataframe, you can access a specific column or row using its label or index.\n",
+    "# Example of indexing in a list\n",
+    "my_list = [10, 20, 30, 40, 50]\n",
+    "print(my_list[0])  # Output: 10\n",
+    "# Example of indexing in a dataframe\n",
+    "import pandas as pd\n",
+    "data = {'Name': ['Alice', 'Bob', 'Charlie'], 'Age': [25, 30, 35]}\n",
+    "df = pd.DataFrame(data)\n",
+    "print(df['Name'][0])  # Output: Alice\n",
+    "# Slicing\n",
+    "# Slicing is used to access a range of elements in a data structure.\n",
+    "# For example, in a list, you can access a sublist using a range of indices.\n",
+    "# In a dataframe, you can access a subset of rows or columns using slicing.\n",
+    "# Example of slicing in a list\n",
+    "my_list = [10, 20, 30, 40, 50]\n",
+    "print(my_list[1:4])  # Output: [20, 30, 40]\n",
+    "# Example of slicing in a dataframe\n",
+    "import pandas as pd\n",
+    "data = {'Name': ['Alice', 'Bob', 'Charlie'], 'Age': [25, 30, 35]}\n",
+    "df = pd.DataFrame(data)\n",
+    "print(df[1:3])  # Output: DataFrame with rows 1 and 2\n",
+    "# Filtering\n",
+    "# Filtering is used to access elements that meet certain conditions.\n",
+    "# For example, in a list, you can filter elements based on a condition.\n",
+    "# In a dataframe, you can filter rows based on column values.\n",
+    "# Example of filtering in a list\n",
+    "my_list = [10, 20, 30, 40, 50]\n",
+    "filtered_list = [x for x in my_list if x > 30]\n",
+    "print(filtered_list)  # Output: [40, 50]\n",
+    "# Example of filtering in a dataframe\n",
+    "import pandas as pd\n",
+    "data = {'Name': ['Alice', 'Bob', 'Charlie'], 'Age': [25, 30, 35]}\n",
+    "df = pd.DataFrame(data)\n",
+    "filtered_df = df[df['Age'] > 30]\n",
+    "print(filtered_df)  # Output: DataFrame with rows where Age > 30\n",
+    "# Sorting\n",
+    "# Sorting is used to arrange elements in a specific order.\n",
+    "# For example, in a list, you can sort the elements in ascending or descending order.\n",
+    "# In a dataframe, you can sort rows based on column values.\n",
+    "# Example of sorting in a list\n",
+    "my_list = [50, 20, 30, 10, 40]\n",
+    "my_list.sort()\n",
+    "print(my_list)  # Output: [10, 20, 30, 40, 50]\n",
+    "# Example of sorting in a dataframe\n",
+    "import pandas as pd\n",
+    "data = {'Name': ['Alice', 'Bob', 'Charlie'], 'Age': [25, 30, 35]}\n",
+    "df = pd.DataFrame(data)\n",
+    "df_sorted = df.sort_values(by='Age')\n",
+    "print(df_sorted)  # Output: DataFrame sorted by Age\n",
+    "# Example of sorting in a dataframe with multiple columns\n",
+    "df_sorted_multi = df.sort_values(by=['Age', 'Name'])\n",
+    "print(df_sorted_multi)  # Output: DataFrame sorted by Age, then by Name\n",
+    "\n",
+    "\n",
+    "# Calculating values\n",
+    "- Via loops\n",
+    "- Via functions\n",
+    "# Calculating values\n",
+    "# Calculating values can be done using loops or functions.\n",
+    "# Example of calculating values using a loop\n",
+    "my_list = [1, 2, 3, 4, 5]\n",
+    "sum_value = 0\n",
+    "for num in my_list:\n",
+    "    sum_value += num\n",
+    "print(sum_value)  # Output: 15\n",
+    "# Example of calculating values using a function\n",
+    "def calculate_sum(numbers):\n",
+    "    return sum(numbers)\n",
+    "my_list = [1, 2, 3, 4, 5]\n",
+    "result = calculate_sum(my_list)\n",
+    "print(result)  # Output: 15\n",
+    "# Example of calculating values using a lambda function\n",
+    "my_list = [1, 2, 3, 4, 5]\n",
+    "calculate_sum_lambda = lambda numbers: sum(numbers)\n",
+    "result_lambda = calculate_sum_lambda(my_list)\n",
+    "print(result_lambda)  # Output: 15\n",
+    "# Example of calculating values using a built-in function\n",
+    "my_list = [1, 2, 3, 4, 5]\n",
+    "result_builtin = sum(my_list)\n",
+    "print(result_builtin)  # Output: 15"
+   ]
+  }
+ ],
+ "metadata": {
+  "language_info": {
+   "name": "python"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}