diff --git a/Assessment/Data_Analytics_with_Python_Assessment.ipynb b/Assessment/Data_Analytics_with_Python_Assessment.ipynb index bfb5557..21005d9 100644 --- a/Assessment/Data_Analytics_with_Python_Assessment.ipynb +++ b/Assessment/Data_Analytics_with_Python_Assessment.ipynb @@ -20,7 +20,6 @@ "SRu7LPAYEOjw", "ZT4ReqO1EWyJ" ], - "authorship_tag": "ABX9TyPxgQWbcz0VylzXsR1503Zj", "include_colab_link": true }, "kernelspec": { @@ -39,7 +38,7 @@ "colab_type": "text" }, "source": [ - "\"Open" + "\"Open" ] }, { @@ -100,13 +99,16 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 22, "metadata": { "id": "4lXTHMaCC8VO" }, "outputs": [], "source": [ - "# Write your code here" + "# Write your code here\n", + "budget = 200\n", + "item_names_list = []\n", + "item_prices_list = []" ] }, { @@ -128,12 +130,28 @@ { "cell_type": "code", "source": [ - "# Write your code here" + "# Write your code here\n", + "def add_item_to_cart(item_name, item_price):\n", + " item_names_list.append(item_name)\n", + " item_prices_list.append(item_price)\n", + " return item_names_list, item_prices_list\n", + "\n", + "\n", + "def calculate_total(item_prices):\n", + " total = sum(item_prices)\n", + " if total > budget:\n", + " print(\"Budget exceeded!\")\n", + " return 0\n", + " elif total < budget and total > 100:\n", + " discount = total * 0.1\n", + " total -= discount\n", + " print(f\"Discounted total: ${total}\")\n", + " return total\n" ], "metadata": { "id": "g_UiAVHSD3UK" }, - "execution_count": null, + "execution_count": 23, "outputs": [] }, { @@ -154,24 +172,88 @@ { "cell_type": "code", "source": [ - "# Write your code here" + "# Write your code here\n", + "start = input(\"Type 'start' to begin: \")" ], "metadata": { - "id": "CJtjsE8YD6Mv" + "id": "CJtjsE8YD6Mv", + "outputId": "2c6e2f0c-e394-49e3-a644-658e8b76c7d0", + "colab": { + "base_uri": "https://localhost:8080/" + } }, - "execution_count": null, - "outputs": [] + "execution_count": 24, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Type 'start' to begin: start\n" + ] + } + ] }, { "cell_type": "code", "source": [ - "# Write your code here" + "\n", + "# Write your code here\n", + "while start == 'start':\n", + " item_name = input(\"Enter item name: \")\n", + " item_price = float(input(\"Enter item price: \"))\n", + " add_item_to_cart(item_name, item_price)\n", + " total = calculate_total(item_prices_list)\n", + " user_input = input(\"Enter 'done' to stop or press Enter to add another item: \")\n", + " if user_input == 'done':\n", + " break\n", + "\n", + "initial_total = sum(item_prices_list)\n", + "final_total = calculate_total(item_prices_list)\n", + "\n", + "print(\"\\nFinal Cart:\")\n", + "for i in range(len(item_names_list)):\n", + " print(f\"{item_names_list[i]}: ${item_prices_list[i]:.2f}\")\n", + "print(f\"Initial Total: ${initial_total:.2f}\")\n", + "if final_total < initial_total:\n", + " print(f\"Discount Applied: -${initial_total - final_total:.2f}\")\n", + "print(f\"Final Total: ${final_total:.2f}\")\n" ], "metadata": { - "id": "M9IlBMeDEOxd" + "id": "M9IlBMeDEOxd", + "outputId": "2566245a-1885-41ec-a2a7-b556606c6570", + "colab": { + "base_uri": "https://localhost:8080/" + } }, - "execution_count": null, - "outputs": [] + "execution_count": 25, + "outputs": [ + { + "output_type": "stream", + "name": "stdout", + "text": [ + "Enter item name: laptop\n", + "Enter item price: 120\n", + "Discounted total: $108.0\n", + "Enter 'done' to stop or press Enter to add another item: \n", + "Enter item name: cheese\n", + "Enter item price: 50\n", + "Discounted total: $153.0\n", + "Enter 'done' to stop or press Enter to add another item: \n", + "Enter item name: shirt\n", + "Enter item price: 60\n", + "Budget exceeded!\n", + "Enter 'done' to stop or press Enter to add another item: done\n", + "\n", + "Final Cart:\n", + "laptop: $120.00\n", + "cheese: $50.00\n", + "shirt: $60.00\n", + "Initial Total: $230.00\n", + "Discount Applied: -$230.00\n", + "Final Total: $0.00\n" + ] + } + ] }, { "cell_type": "markdown", @@ -200,12 +282,15 @@ { "cell_type": "code", "source": [ - "# Import necessary modules and libraries" + "# Import necessary modules and libraries\n", + "import pandas as pd\n", + "import numpy as np\n", + "import matplotlib.pyplot as plt" ], "metadata": { "id": "zX8_bEfKSGcB" }, - "execution_count": null, + "execution_count": 27, "outputs": [] }, { @@ -222,13 +307,60 @@ { "cell_type": "code", "source": [ - "# Write code here" + "# Write code here\n", + "url = 'https://raw.githubusercontent.com/magatrons/PythonDA-course/refs/heads/main/Assessment/dataset.csv'\n", + "df = pd.read_csv(url)\n", + "df.head()\n", + "df.info()\n", + "# The dataset contains the following structure:\n", + "# - Rows: Represents individual entries, the total number of rows can be determined from the data.info() output.\n", + "# - Columns: Each column represents a variable in the dataset.\n", + "# - Data types: The data.info() output will detail the types (e.g., int64, float64, object).\n", + "# Example columns might include patient health indicators, diagnosis results, or other related features." ], "metadata": { - "id": "iN_Ne4xKSE_g" + "id": "iN_Ne4xKSE_g", + "outputId": "1e7cec65-b81b-4d95-eada-550513d2ee98", + "colab": { + "base_uri": "https://localhost:8080/" + } }, - "execution_count": null, - "outputs": [] + "execution_count": 29, + "outputs": [ + { + "output_type": "stream", + "name": "stdout", + "text": [ + "\n", + "RangeIndex: 5000 entries, 0 to 4999\n", + "Data columns (total 20 columns):\n", + " # Column Non-Null Count Dtype \n", + "--- ------ -------------- ----- \n", + " 0 Employee_ID 5000 non-null object\n", + " 1 Age 5000 non-null int64 \n", + " 2 Gender 5000 non-null object\n", + " 3 Job_Role 5000 non-null object\n", + " 4 Industry 5000 non-null object\n", + " 5 Years_of_Experience 5000 non-null int64 \n", + " 6 Work_Location 5000 non-null object\n", + " 7 Hours_Worked_Per_Week 5000 non-null int64 \n", + " 8 Number_of_Virtual_Meetings 5000 non-null int64 \n", + " 9 Work_Life_Balance_Rating 5000 non-null int64 \n", + " 10 Stress_Level 5000 non-null object\n", + " 11 Mental_Health_Condition 3804 non-null object\n", + " 12 Access_to_Mental_Health_Resources 5000 non-null object\n", + " 13 Productivity_Change 5000 non-null object\n", + " 14 Social_Isolation_Rating 5000 non-null int64 \n", + " 15 Satisfaction_with_Remote_Work 5000 non-null object\n", + " 16 Company_Support_for_Remote_Work 5000 non-null int64 \n", + " 17 Physical_Activity 3371 non-null object\n", + " 18 Sleep_Quality 5000 non-null object\n", + " 19 Region 5000 non-null object\n", + "dtypes: int64(7), object(13)\n", + "memory usage: 781.4+ KB\n" + ] + } + ] }, { "cell_type": "markdown", @@ -243,13 +375,694 @@ { "cell_type": "code", "source": [ - "# Write code here" + "# Write code here\n", + "df.head(13)" ], "metadata": { - "id": "aojeUCP3-DlN" + "id": "aojeUCP3-DlN", + "outputId": "c6b065e3-fe70-4f02-fbf1-a22822f83107", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 693 + } }, - "execution_count": null, - "outputs": [] + "execution_count": 30, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + " Employee_ID Age Gender Job_Role Industry \\\n", + "0 EMP0001 32 Non-binary HR Healthcare \n", + "1 EMP0002 40 Female Data Scientist IT \n", + "2 EMP0003 59 Non-binary Software Engineer Education \n", + "3 EMP0004 27 Male Software Engineer Finance \n", + "4 EMP0005 49 Male Sales Consulting \n", + "5 EMP0006 59 Non-binary Sales IT \n", + "6 EMP0007 31 Prefer not to say Sales IT \n", + "7 EMP0008 42 Non-binary Data Scientist Manufacturing \n", + "8 EMP0009 56 Prefer not to say Data Scientist Healthcare \n", + "9 EMP0010 30 Female HR IT \n", + "10 EMP0011 33 Non-binary Software Engineer Finance \n", + "11 EMP0012 47 Female Marketing Consulting \n", + "12 EMP0013 40 Female Marketing Consulting \n", + "\n", + " Years_of_Experience Work_Location Hours_Worked_Per_Week \\\n", + "0 13 Hybrid 47 \n", + "1 3 Remote 52 \n", + "2 22 Hybrid 46 \n", + "3 20 Onsite 32 \n", + "4 32 Onsite 35 \n", + "5 31 Hybrid 39 \n", + "6 24 Remote 51 \n", + "7 6 Onsite 54 \n", + "8 9 Hybrid 24 \n", + "9 28 Hybrid 57 \n", + "10 17 Remote 48 \n", + "11 31 Hybrid 26 \n", + "12 1 Remote 21 \n", + "\n", + " Number_of_Virtual_Meetings Work_Life_Balance_Rating Stress_Level \\\n", + "0 7 2 Medium \n", + "1 4 1 Medium \n", + "2 11 5 Medium \n", + "3 8 4 High \n", + "4 12 2 High \n", + "5 3 4 High \n", + "6 7 3 Low \n", + "7 7 3 Medium \n", + "8 4 2 High \n", + "9 6 1 Low \n", + "10 3 3 High \n", + "11 12 4 Medium \n", + "12 7 2 High \n", + "\n", + " Mental_Health_Condition Access_to_Mental_Health_Resources \\\n", + "0 Depression No \n", + "1 Anxiety No \n", + "2 Anxiety No \n", + "3 Depression Yes \n", + "4 NaN Yes \n", + "5 NaN No \n", + "6 Anxiety Yes \n", + "7 Depression No \n", + "8 NaN Yes \n", + "9 Depression Yes \n", + "10 NaN Yes \n", + "11 NaN Yes \n", + "12 Depression Yes \n", + "\n", + " Productivity_Change Social_Isolation_Rating Satisfaction_with_Remote_Work \\\n", + "0 Decrease 1 Unsatisfied \n", + "1 Increase 3 Satisfied \n", + "2 No Change 4 Unsatisfied \n", + "3 Increase 3 Unsatisfied \n", + "4 Decrease 3 Unsatisfied \n", + "5 Increase 5 Unsatisfied \n", + "6 Decrease 5 Neutral \n", + "7 Decrease 5 Satisfied \n", + "8 Decrease 2 Unsatisfied \n", + "9 Decrease 2 Neutral \n", + "10 Decrease 4 Satisfied \n", + "11 No Change 4 Neutral \n", + "12 Decrease 2 Neutral \n", + "\n", + " Company_Support_for_Remote_Work Physical_Activity Sleep_Quality \\\n", + "0 1 Weekly Good \n", + "1 2 Weekly Good \n", + "2 5 NaN Poor \n", + "3 3 NaN Poor \n", + "4 3 Weekly Average \n", + "5 1 NaN Average \n", + "6 3 Daily Poor \n", + "7 4 NaN Average \n", + "8 4 Daily Poor \n", + "9 1 Weekly Poor \n", + "10 2 Weekly Average \n", + "11 3 Weekly Poor \n", + "12 1 Weekly Good \n", + "\n", + " Region \n", + "0 Europe \n", + "1 Asia \n", + "2 North America \n", + "3 Europe \n", + "4 North America \n", + "5 South America \n", + "6 Asia \n", + "7 North America \n", + "8 Europe \n", + "9 North America \n", + "10 Oceania \n", + "11 Africa \n", + "12 Europe " + ], + "text/html": [ + "\n", + "
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