{"id":1464,"date":"2025-07-11T03:27:26","date_gmt":"2025-07-11T03:27:26","guid":{"rendered":"https:\/\/itxperts.co.in\/blog\/?p=1464"},"modified":"2025-07-11T03:27:57","modified_gmt":"2025-07-11T03:27:57","slug":"informatics-practices-exam-questions-to-score-high-marks","status":"publish","type":"post","link":"https:\/\/itxperts.co.in\/blog\/informatics-practices-exam-questions-to-score-high-marks\/","title":{"rendered":"Informatics Practices Exam Questions to Score High Marks"},"content":{"rendered":"\n<blockquote class=\"wp-block-quote is-layout-flow wp-block-quote-is-layout-flow\">\n<p>Here&#8217;s a list of important questions and answers on <strong>Python, Pandas, and Matplotlib<\/strong>. Use them to practice for your Class 11 and 12 board exams and get better marks.<\/p>\n<\/blockquote>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<h3 class=\"wp-block-heading\"><strong>How to Use These Questions<\/strong><\/h3>\n\n\n\n<h4 class=\"wp-block-heading\"><strong>For Students \ud83e\uddd1\u200d\ud83c\udf93<\/strong><\/h4>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Test Yourself:<\/strong> First, try to answer the question on your own. Then, check the solution.<\/li>\n\n\n\n<li><strong>Find Weak Topics:<\/strong> Pay attention to the questions you get wrong. This tells you what you need to study more.<\/li>\n\n\n\n<li><strong>Prepare for Exams:<\/strong> These questions are like the ones that come in the board exam, so they are great practice.<\/li>\n<\/ul>\n\n\n\n<h4 class=\"wp-block-heading\"><strong>For Teachers \ud83e\uddd1\u200d\ud83c\udfeb<\/strong><\/h4>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Make Class Tests:<\/strong> You can use these questions to easily create quizzes and tests for your students.<\/li>\n\n\n\n<li><strong>Give for Revision:<\/strong> Share this list with students to help them revise everything before the final exam.<\/li>\n\n\n\n<li><strong>Discuss in Class:<\/strong> Use the tricky questions as examples to explain difficult topics in the classroom.<\/li>\n<\/ul>\n\n\n\n<h3 class=\"wp-block-heading\"><strong><span style=\"text-decoration: underline;\">Python Fundamentals<\/span><\/strong><\/h3>\n\n\n\n<p><strong>1. What is the difference between a list and a tuple in Python?<\/strong> A <strong>list<\/strong> is mutable, meaning you can change its contents (add, remove, or modify elements). A <strong>tuple<\/strong> is immutable, meaning once it&#8217;s created, you cannot change its elements.<\/p>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<p><strong>2. What are the key features of Python?<\/strong> Python&#8217;s key features include its <strong>simple and readable syntax<\/strong>, <strong>dynamic typing<\/strong> (no need to declare variable types), being an <strong>interpreted language<\/strong> (executed line by line), and having a <strong>large standard library<\/strong>.<\/p>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<p><strong>3. How do you write comments in Python?<\/strong> You use the hash symbol (<code>#<\/code>) for single-line comments. For multi-line comments, you can enclose the text in triple quotes (<code>\"\"\"...\"\"\"<\/code> or <code>'''...'''<\/code>).<\/p>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<p><strong>4. What are the main data types in Python?<\/strong> The main data types are:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Numeric:<\/strong> <code>int<\/code> (integers), <code>float<\/code> (floating-point numbers)<\/li>\n\n\n\n<li><strong>Text:<\/strong> <code>str<\/code> (strings)<\/li>\n\n\n\n<li><strong>Sequence:<\/strong> <code>list<\/code>, <code>tuple<\/code><\/li>\n\n\n\n<li><strong>Mapping:<\/strong> <code>dict<\/code> (dictionaries)<\/li>\n\n\n\n<li><strong>Boolean:<\/strong> <code>bool<\/code> (<code>True<\/code> or <code>False<\/code>)<\/li>\n<\/ul>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<p><strong>5. How do you open and close a file in Python safely?<\/strong> The best way is to use the <code>with<\/code> statement, as it automatically handles closing the file even if errors occur.<\/p>\n\n\n\n<pre class=\"wp-block-code\"><code>with open('data.txt', 'r') as file:\n    content = file.read()\n<\/code><\/pre>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<p><strong>6. What is the difference between the <code>=<\/code> and <code>==<\/code> operators?<\/strong> The <code>=<\/code> operator is for <strong>assignment<\/strong> (e.g., <code>x = 5<\/code> assigns the value 5 to x). The <code>==<\/code> operator is for <strong>comparison<\/strong> (e.g., <code>x == 5<\/code> checks if the value of x is equal to 5).<\/p>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<p><strong>7. Explain the <code>break<\/code> and <code>continue<\/code> statements in a loop.<\/strong><\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><code>break<\/code>: Immediately <strong>terminates<\/strong> the entire loop and the program continues with the next statement after the loop.<\/li>\n\n\n\n<li><code>continue<\/code>: <strong>Skips<\/strong> the current iteration of the loop and immediately proceeds to the next iteration.<\/li>\n<\/ul>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<p><strong>8. What is a dictionary in Python? Give an example.<\/strong> A dictionary is an unordered collection that stores data in <strong>key-value pairs<\/strong>.<\/p>\n\n\n\n<pre class=\"wp-block-code\"><code>student = {'name': 'Rohan', 'class': 12, 'stream': 'Science'}\n<\/code><\/pre>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<p><strong>9. How do you define a function in Python?<\/strong> You use the <code>def<\/code> keyword, followed by the function name, parentheses <code>()<\/code>, and a colon <code>:<\/code>.<\/p>\n\n\n\n<pre class=\"wp-block-code\"><code>def calculate_sum(a, b):\n    return a + b\n<\/code><\/pre>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<p><strong>10. What does the <code>len()<\/code> function do?<\/strong> The <code>len()<\/code> function returns the number of items (length) in an object like a string, list, or dictionary.<\/p>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<h3 class=\"wp-block-heading\"><strong>Pandas<\/strong><\/h3>\n\n\n\n<p><strong>11. What is Pandas used for in Python?<\/strong> Pandas is a library used for <strong>data manipulation and analysis<\/strong>. It provides data structures and functions needed to work with structured data seamlessly.<\/p>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<p><strong>12. What are the two primary data structures in Pandas?<\/strong> The two main data structures are the <strong>Series<\/strong> (a 1D labeled array) and the <strong>DataFrame<\/strong> (a 2D labeled table with columns of potentially different types).<\/p>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<style>\n  .py-promo-box {\n    background-color: #f8f9fa;\n    border-left: 5px solid #4B8BBE;\n    border-radius: 5px;\n    padding: 25px;\n    margin: 30px 0;\n    text-align: center;\n    font-family: sans-serif;\n    box-shadow: 0 2px 8px rgba(0,0,0,0.1);\n  }\n  .py-promo-box h3 {\n    margin-top: 0;\n    color: #333;\n    font-size: 20px;\n  }\n  .py-promo-box p {\n    color: #555;\n    font-size: 16px;\n    margin-bottom: 20px;\n  }\n  .py-promo-box .py-button {\n    display: inline-block;\n    background-color: #FFD43B;\n    color: #3D4A5D;\n    padding: 12px 25px;\n    text-decoration: none;\n    font-weight: bold;\n    border-radius: 5px;\n    transition: background-color 0.3s ease;\n  }\n  .py-promo-box .py-button:hover {\n    background-color: #fcc700;\n  }\n<\/style>\n\n<div class=\"py-promo-box\">\n  <h3>Test Your Python Code Instantly \ud83d\ude80<\/h3>\n  <p>Want to try out the code yourself? Use our free AI-based Python IDLE right in your browser\u2014no installation needed!<\/p>\n  <a href=\"https:\/\/itxperts.co.in\/PYTHON-AI-IDLE\/\" class=\"py-button\" target=\"_blank\" rel=\"noopener noreferrer\">\n    Launch Free Python IDLE\n  <\/a>\n<\/div>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<p><strong>13. How do you create a Pandas Series from a Python list?<\/strong><\/p>\n\n\n\n<pre class=\"wp-block-code\"><code>import pandas as pd\nmy_list = &#91;10, 20, 30, 40]\nmy_series = pd.Series(my_list)\nprint(my_series)\n<\/code><\/pre>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<p><strong>14. How do you create a Pandas DataFrame from a dictionary?<\/strong><\/p>\n\n\n\n<pre class=\"wp-block-code\"><code>import pandas as pd\ndata = {'Name': &#91;'Aisha', 'Ben', 'Carla'], 'Marks': &#91;85, 92, 78]}\ndf = pd.DataFrame(data)\nprint(df)\n<\/code><\/pre>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<p><strong>15. What is the use of the <code>head()<\/code> and <code>tail()<\/code> methods?<\/strong><\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><code>head(n)<\/code>: Returns the <strong>first <code>n<\/code> rows<\/strong> of a DataFrame (5 by default).<\/li>\n\n\n\n<li><code>tail(n)<\/code>: Returns the <strong>last <code>n<\/code> rows<\/strong> of a DataFrame (5 by default).<\/li>\n<\/ul>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<p><strong>16. How do you read a CSV file into a Pandas DataFrame?<\/strong> You use the <code>pd.read_csv()<\/code> function.<\/p>\n\n\n\n<pre class=\"wp-block-code\"><code>import pandas as pd\ndf = pd.read_csv('students.csv')\n<\/code><\/pre>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<p><strong>17. How do you select a single column named &#8216;Marks&#8217; from a DataFrame <code>df<\/code>?<\/strong> You can use square brackets:<\/p>\n\n\n\n<pre class=\"wp-block-code\"><code>marks_column = df&#91;'Marks']\n<\/code><\/pre>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<p><strong>18. How do you select multiple columns, &#8216;Name&#8217; and &#8216;Marks&#8217;, from a DataFrame <code>df<\/code>?<\/strong> You pass a list of column names inside the square brackets.<\/p>\n\n\n\n<pre class=\"wp-block-code\"><code>subset_df = df&#91;&#91;'Name', 'Marks']]\n<\/code><\/pre>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<p><strong>19. What is the difference between <code>loc<\/code> and <code>iloc<\/code>?<\/strong><\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><code>loc<\/code>: Selects data based on <strong>labels<\/strong> (index names, column names).<\/li>\n\n\n\n<li><code>iloc<\/code>: Selects data based on <strong>integer position<\/strong> (row and column number).<\/li>\n<\/ul>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<p><strong>20. How would you add a new column named &#8216;Grade&#8217; to a DataFrame <code>df<\/code>?<\/strong><\/p>\n\n\n\n<pre class=\"wp-block-code\"><code>df&#91;'Grade'] = &#91;'A', 'A+', 'B']\n<\/code><\/pre>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<p><strong>21. How can you handle missing data in a DataFrame?<\/strong> You can use <code>dropna()<\/code> to <strong>remove rows\/columns<\/strong> with missing values or <code>fillna(value)<\/code> to <strong>fill missing values<\/strong> with a specific <code>value<\/code>.<\/p>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<p><strong>22. What does the <code>groupby()<\/code> method do?<\/strong> The <code>groupby()<\/code> method is used to <strong>split the data into groups<\/strong> based on some criteria, apply a function (like <code>sum()<\/code>, <code>mean()<\/code>) to each group, and then combine the results.<\/p>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<p><strong>23. How do you get a summary of statistics for a DataFrame <code>df<\/code>?<\/strong> Use the <code>describe()<\/code> method. It provides statistics like count, mean, std, min, and max for numeric columns.<\/p>\n\n\n\n<pre class=\"wp-block-code\"><code>print(df.describe())\n<\/code><\/pre>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<p><strong>24. How do you rename a column from &#8216;Marks&#8217; to &#8216;Score&#8217; in a DataFrame <code>df<\/code>?<\/strong> Use the <code>rename()<\/code> method.<\/p>\n\n\n\n<pre class=\"wp-block-code\"><code>df = df.rename(columns={'Marks': 'Score'})\n<\/code><\/pre>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<p><strong>25. How do you sort a DataFrame <code>df<\/code> based on the &#8216;Marks&#8217; column in descending order?<\/strong> Use the <code>sort_values()<\/code> method.<\/p>\n\n\n\n<pre class=\"wp-block-code\"><code>df_sorted = df.sort_values(by='Marks', ascending=False)\n<\/code><\/pre>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<h3 class=\"wp-block-heading\"><strong>Matplotlib<\/strong><\/h3>\n\n\n\n<p><strong>26. What is Matplotlib?<\/strong> Matplotlib is a <strong>plotting library<\/strong> for Python used to create high-quality static, animated, and interactive visualizations and graphs.<\/p>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<p><strong>27. What is Pyplot?<\/strong> <code>pyplot<\/code> is a collection of functions within Matplotlib that provides a simple interface for creating plots, similar to MATLAB. It&#8217;s typically imported as <code>plt<\/code>.<\/p>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<p><strong>28. How do you create a basic line plot?<\/strong><\/p>\n\n\n\n<pre class=\"wp-block-code\"><code>import matplotlib.pyplot as plt\nx = &#91;1, 2, 3, 4]\ny = &#91;2, 4, 6, 8]\nplt.plot(x, y)\nplt.show()\n<\/code><\/pre>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<p><strong>29. How do you create a bar chart?<\/strong><\/p>\n\n\n\n<pre class=\"wp-block-code\"><code>import matplotlib.pyplot as plt\nsubjects = &#91;'Physics', 'Chemistry', 'Math']\nmarks = &#91;88, 91, 95]\nplt.bar(subjects, marks)\nplt.show()\n<\/code><\/pre>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<p><strong>30. How would you create a histogram for a list of numbers <code>data<\/code>?<\/strong><\/p>\n\n\n\n<pre class=\"wp-block-code\"><code>import matplotlib.pyplot as plt\ndata = &#91;80, 85, 90, 91, 92, 95, 98, 100]\nplt.hist(data, bins=5)\nplt.show()\n<\/code><\/pre>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<p><strong>31. How do you add a title and labels for the X and Y axes?<\/strong><\/p>\n\n\n\n<pre class=\"wp-block-code\"><code>plt.title(\"Student Performance\")\nplt.xlabel(\"Subjects\")\nplt.ylabel(\"Marks Obtained\")\n<\/code><\/pre>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<p><strong>32. How do you create a scatter plot?<\/strong><\/p>\n\n\n\n<pre class=\"wp-block-code\"><code>import matplotlib.pyplot as plt\nstudy_hours = &#91;2, 3, 5, 1, 6]\nexam_scores = &#91;65, 70, 85, 60, 90]\nplt.scatter(study_hours, exam_scores)\nplt.show()\n<\/code><\/pre>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<p><strong>33. How do you add a legend to a plot?<\/strong> You must add a <code>label<\/code> to each plot command and then call <code>plt.legend()<\/code>.<\/p>\n\n\n\n<pre class=\"wp-block-code\"><code>plt.plot(x1, y1, label='Class A')\nplt.plot(x2, y2, label='Class B')\nplt.legend()\n<\/code><\/pre>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<p><strong>34. How do you save a plot to an image file?<\/strong> Use the <code>savefig()<\/code> function before <code>show()<\/code>.<\/p>\n\n\n\n<pre class=\"wp-block-code\"><code>plt.savefig('my_chart.png')\n<\/code><\/pre>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<p><strong>35. How do you create a pie chart?<\/strong><\/p>\n\n\n\n<pre class=\"wp-block-code\"><code>import matplotlib.pyplot as plt\nlabels = &#91;'India', 'China', 'USA']\npopulation = &#91;139, 144, 33]\nplt.pie(population, labels=labels, autopct='%1.1f%%')\nplt.axis('equal') # Ensures the pie is circular\nplt.show()\n<\/code><\/pre>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<p><strong>36. How do you change the color and style of a line in a plot?<\/strong> Pass the <code>color<\/code> and <code>linestyle<\/code> arguments to the <code>plot()<\/code> function.<\/p>\n\n\n\n<pre class=\"wp-block-code\"><code>plt.plot(x, y, color='green', linestyle='--')\n<\/code><\/pre>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<p><strong>37. How can you create multiple plots in one figure?<\/strong> Use the <code>subplot()<\/code> function. For example, <code>plt.subplot(1, 2, 1)<\/code> creates a figure with 1 row, 2 columns and sets the first plot as active.<\/p>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<p><strong>38. What is the purpose of <code>plt.show()<\/code>?<\/strong> <code>plt.show()<\/code> <strong>displays<\/strong> all the figures you have created. It should typically be called once at the end of your script.<\/p>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<p><strong>39. How do you set the size of a figure?<\/strong> Use <code>plt.figure(figsize=(width, height))<\/code>. For example:<\/p>\n\n\n\n<pre class=\"wp-block-code\"><code>plt.figure(figsize=(10, 6)) # 10 inches wide, 6 inches tall\n<\/code><\/pre>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<p><strong>40. How do you create a horizontal bar chart?<\/strong> Use the <code>plt.barh()<\/code> function instead of <code>plt.bar()<\/code>.<\/p>\n\n\n\n<pre class=\"wp-block-code\"><code>plt.barh(subjects, marks)\n<\/code><\/pre>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<h3 class=\"wp-block-heading\"><strong>Mixed Practice Questions<\/strong><\/h3>\n\n\n\n<p><strong>41. Write code to read a CSV file &#8216;data.csv&#8217; into a DataFrame and display its first 5 rows.<\/strong><\/p>\n\n\n\n<pre class=\"wp-block-code\"><code>import pandas as pd\ndf = pd.read_csv('data.csv')\nprint(df.head())\n<\/code><\/pre>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<p><strong>42. Given a DataFrame <code>df<\/code> with a column &#8216;Price&#8217;, create a new column &#8216;Tax&#8217; that is 18% of the &#8216;Price&#8217;.<\/strong><\/p>\n\n\n\n<pre class=\"wp-block-code\"><code>df&#91;'Tax'] = df&#91;'Price'] * 0.18\n<\/code><\/pre>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<p><strong>43. Write the code to create a line plot for the &#8216;Temperature&#8217; column from a DataFrame <code>df<\/code>. Add the title &#8220;Daily Temperature&#8221;.<\/strong><\/p>\n\n\n\n<pre class=\"wp-block-code\"><code>import matplotlib.pyplot as plt\nplt.plot(df&#91;'Temperature'])\nplt.title(\"Daily Temperature\")\nplt.ylabel(\"Temperature (Celsius)\")\nplt.show()\n<\/code><\/pre>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<p><strong>44. How do you find the total number of rows and columns in a DataFrame <code>df<\/code>?<\/strong> Use the <code>shape<\/code> attribute. It returns a tuple <code>(rows, columns)<\/code>.<\/p>\n\n\n\n<pre class=\"wp-block-code\"><code>print(df.shape)\n<\/code><\/pre>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<p><strong>45. Write code to group a DataFrame <code>df<\/code> by &#8216;City&#8217; and find the average &#8216;Salary&#8217; for each city.<\/strong><\/p>\n\n\n\n<pre class=\"wp-block-code\"><code>avg_salary_by_city = df.groupby('City')&#91;'Salary'].mean()\nprint(avg_salary_by_city)\n<\/code><\/pre>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<p><strong>46. How do you drop a column named &#8216;Redundant&#8217; from a DataFrame <code>df<\/code>?<\/strong><\/p>\n\n\n\n<pre class=\"wp-block-code\"><code>df.drop('Redundant', axis=1, inplace=True)\n# axis=1 specifies column, inplace=True modifies the DataFrame directly\n<\/code><\/pre>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<p><strong>47. Write code to create a bar chart showing the average salary for each city calculated in the previous question.<\/strong><\/p>\n\n\n\n<pre class=\"wp-block-code\"><code>import matplotlib.pyplot as plt\navg_salary_by_city.plot(kind='bar', color='skyblue')\nplt.ylabel('Average Salary')\nplt.title('Average Salary by City')\nplt.show()\n<\/code><\/pre>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<p><strong>48. How do you select rows from a DataFrame <code>df<\/code> where the &#8216;Age&#8217; is greater than 30?<\/strong><\/p>\n\n\n\n<pre class=\"wp-block-code\"><code>senior_employees = df&#91;df&#91;'Age'] &gt; 30]\n<\/code><\/pre>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<p><strong>49. What is the output of the following code?<\/strong><\/p>\n\n\n\n<pre class=\"wp-block-code\"><code>import pandas as pd\ns = pd.Series(&#91;10, 20, 30], index=&#91;'x', 'y', 'z'])\nprint(s&#91;'y'])\n<\/code><\/pre>\n\n\n\n<p>Output:<\/p>\n\n\n\n<pre class=\"wp-block-code\"><code>20\n<\/code><\/pre>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<p><strong>50. Write code to create a scatter plot of &#8216;StudyHours&#8217; vs &#8216;Marks&#8217; from a DataFrame <code>df<\/code>.<\/strong><\/p>\n\n\n\n<pre class=\"wp-block-code\"><code>import matplotlib.pyplot as plt\nplt.scatter(df&#91;'StudyHours'], df&#91;'Marks'])\nplt.xlabel('Hours Studied')\nplt.ylabel('Marks Obtained')\nplt.title('Study Hours vs. Marks')\nplt.show()\n<\/code><\/pre>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<p><strong>51. How do you find and count the number of missing (NaN) values in each column of a DataFrame <code>df<\/code>?<\/strong><\/p>\n\n\n\n<pre class=\"wp-block-code\"><code>print(df.isnull().sum())<\/code><\/pre>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<h3 class=\"wp-block-heading\"><strong><span style=\"text-decoration: underline;\">Output Prediction &amp; Error Finding<\/span><\/strong><\/h3>\n\n\n\n<p><strong>1. What will be the output of the following Python code?<\/strong><\/p>\n\n\n\n<pre class=\"wp-block-code\"><code>my_tuple = (10, 20, 30, 40)\n# my_tuple&#91;1] = 25\nprint(len(my_tuple))\n<\/code><\/pre>\n\n\n\n<p>The code will raise a <strong>TypeError<\/strong> because tuples are immutable and the line <code>my_tuple[1] = 25<\/code> attempts to change an element. If that line were commented out or removed, the output would be <code>4<\/code>.<\/p>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<p><strong>2. Predict the output of the following Pandas code.<\/strong><\/p>\n\n\n\n<pre class=\"wp-block-code\"><code>import pandas as pd\ns1 = pd.Series(&#91;1, 2, 3])\ns2 = pd.Series(&#91;10, 20, 30])\nprint(s1 + s2)\n<\/code><\/pre>\n\n\n\n<p><strong>Output:<\/strong><\/p>\n\n\n\n<pre class=\"wp-block-code\"><code>0    11\n1    22\n2    33\ndtype: int64\n<\/code><\/pre>\n\n\n\n<p>The series are added element-wise based on their integer index.<\/p>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<p><strong>3. Find the error in the following code to create a DataFrame.<\/strong><\/p>\n\n\n\n<pre class=\"wp-block-code\"><code>import pandas as pd\ndata = {'Name': &#91;'Sid', 'Ria', 'Tom'], 'Score': &#91;88, 91]}\ndf = pd.DataFrame(data)\nprint(df)\n<\/code><\/pre>\n\n\n\n<p>The code will raise a <strong>ValueError<\/strong>. The error is that the lists provided for the dictionary values have different lengths (&#8216;Name&#8217; has 3 elements, but &#8216;Score&#8217; has 2). All arrays must be of the same length.<\/p>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<p><strong>4. What is the output of the following code?<\/strong><\/p>\n\n\n\n<pre class=\"wp-block-code\"><code>import pandas as pd\ndf = pd.DataFrame({'A': &#91;1, 2, 3], 'B': &#91;4, 5, 6]}, index=&#91;'x', 'y', 'z'])\nprint(df.iloc&#91;1, 1])\n<\/code><\/pre>\n\n\n\n<p><strong>Output:<\/strong><\/p>\n\n\n\n<pre class=\"wp-block-code\"><code>5\n<\/code><\/pre>\n\n\n\n<p><code>iloc[1, 1]<\/code> accesses the element at the second row (integer position 1) and second column (integer position 1).<\/p>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<p><strong>5. What is the output of the following?<\/strong><\/p>\n\n\n\n<pre class=\"wp-block-code\"><code>import pandas as pd\ndf = pd.DataFrame({'A': &#91;1, 2, 3], 'B': &#91;4, 5, 6]}, index=&#91;'x', 'y', 'z'])\nprint(df.loc&#91;'y'])\n<\/code><\/pre>\n\n\n\n<p><strong>Output:<\/strong><\/p>\n\n\n\n<pre class=\"wp-block-code\"><code>A    2\nB    5\nName: y, dtype: int64\n<\/code><\/pre>\n\n\n\n<p><code>loc['y']<\/code> accesses the row with the label &#8216;y&#8217; and returns it as a Series.<\/p>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<h3 class=\"wp-block-heading\"><strong>Data Manipulation with Pandas<\/strong><\/h3>\n\n\n\n<p><strong>6. Given a DataFrame of student scores, how would you select all students who scored more than 80 in &#8216;Maths&#8217; and more than 85 in &#8216;Science&#8217;?<\/strong><\/p>\n\n\n\n<pre class=\"wp-block-code\"><code># Assuming df has 'Maths' and 'Science' columns\ntop_students = df&#91;(df&#91;'Maths'] &gt; 80) &amp; (df&#91;'Science'] &gt; 85)]\nprint(top_students)\n<\/code><\/pre>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<p><strong>7. You have a DataFrame <code>df<\/code> with a &#8216;DOB&#8217; column containing dates as strings (e.g., &#8216;2005-10-25&#8217;). How do you convert this column to a proper datetime format?<\/strong> You can use the <code>pd.to_datetime()<\/code> function.<\/p>\n\n\n\n<pre class=\"wp-block-code\"><code>df&#91;'DOB'] = pd.to_datetime(df&#91;'DOB'])\n<\/code><\/pre>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<p><strong>8. How can you remove duplicate rows from a DataFrame <code>df<\/code> based on the &#8216;Email&#8217; column?<\/strong> Use the <code>drop_duplicates()<\/code> method.<\/p>\n\n\n\n<pre class=\"wp-block-code\"><code>df.drop_duplicates(subset=&#91;'Email'], inplace=True)\n<\/code><\/pre>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<p><strong>9. You have two DataFrames, <code>df1<\/code> (with student names and IDs) and <code>df2<\/code> (with student IDs and marks). How do you combine them into a single DataFrame based on the student ID?<\/strong> You use the <code>pd.merge()<\/code> function.<\/p>\n\n\n\n<pre class=\"wp-block-code\"><code>merged_df = pd.merge(df1, df2, on='StudentID')\n<\/code><\/pre>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<p><strong>10. How do you find the number of unique values in the &#8216;City&#8217; column of a DataFrame <code>df<\/code>?<\/strong> Use the <code>nunique()<\/code> method.<\/p>\n\n\n\n<pre class=\"wp-block-code\"><code>num_cities = df&#91;'City'].nunique()\nprint(num_cities)\n<\/code><\/pre>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<p><strong>11. How do you replace all occurrences of <code>_<\/code> with a space in the column names of a DataFrame <code>df<\/code>?<\/strong><\/p>\n\n\n\n<pre class=\"wp-block-code\"><code>df.columns = df.columns.str.replace('_', ' ')\n<\/code><\/pre>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<p><strong>12. Given a DataFrame <code>df<\/code>, how do you calculate the correlation between the &#8216;Age&#8217; and &#8216;Salary&#8217; columns?<\/strong> You can use the <code>.corr()<\/code> method.<\/p>\n\n\n\n<pre class=\"wp-block-code\"><code>correlation = df&#91;'Age'].corr(df&#91;'Salary'])\nprint(correlation)\n<\/code><\/pre>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<h3 class=\"wp-block-heading\"><strong>Data Visualization with Matplotlib<\/strong><\/h3>\n\n\n\n<p><strong>13. How do you create a bar chart where the bars have different colors?<\/strong> You can pass a list of colors to the <code>color<\/code> parameter.<\/p>\n\n\n\n<pre class=\"wp-block-code\"><code>import matplotlib.pyplot as plt\nproducts = &#91;'A', 'B', 'C']\nsales = &#91;100, 150, 120]\ncolors = &#91;'red', 'blue', 'green']\nplt.bar(products, sales, color=colors)\nplt.show()\n<\/code><\/pre>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<p><strong>14. How do you add text annotations to specific data points on a plot?<\/strong> <\/p>\n\n\n\n<p>Use the <code>plt.text()<\/code> or <code>ax.annotate()<\/code> functions.<\/p>\n\n\n\n<pre class=\"wp-block-code\"><code>plt.plot(x, y)\n# Add text 'Peak' at the coordinate (x_peak, y_peak)\nplt.text(x_peak, y_peak, 'Peak')\n<\/code><\/pre>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<p><strong>15. Write the code to create two line plots on the same axes, one for &#8216;Sales&#8217; and one for &#8216;Profit&#8217; from a DataFrame <code>df<\/code>. Add a legend to distinguish them.<\/strong><\/p>\n\n\n\n<pre class=\"wp-block-code\"><code>import matplotlib.pyplot as plt\nplt.plot(df&#91;'Month'], df&#91;'Sales'], label='Sales', marker='o')\nplt.plot(df&#91;'Month'], df&#91;'Profit'], label='Profit', marker='x')\nplt.legend()\nplt.show()\n<\/code><\/pre>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<p><strong>16. What is the difference between <code>plt.bar()<\/code> and <code>plt.hist()<\/code>?<\/strong><\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><code>plt.bar()<\/code> is used to plot <strong>categorical data<\/strong> against a numeric value. It requires two arrays (categories and their values).<\/li>\n\n\n\n<li><code>plt.hist()<\/code> is used to visualize the <strong>distribution of continuous numerical data<\/strong>. It takes a single array and divides the data into bins, counting the frequency in each bin.<\/li>\n<\/ul>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<p><strong>17. How do you create a stacked bar chart in Matplotlib?<\/strong> You plot the second dataset with the <code>bottom<\/code> parameter set to the values of the first dataset.<\/p>\n\n\n\n<pre class=\"wp-block-code\"><code>import matplotlib.pyplot as plt\nyears = &#91;'2021', '2022', '2023']\nsales_online = &#91;100, 120, 150]\nsales_offline = &#91;80, 90, 85]\n\nplt.bar(years, sales_online, label='Online')\nplt.bar(years, sales_offline, bottom=sales_online, label='Offline')\nplt.legend()\nplt.show()\n<\/code><\/pre>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<h3 class=\"wp-block-heading\"><strong>Case Study \/ Application Questions<\/strong><\/h3>\n\n\n\n<p><strong>Scenario: A CSV file <code>exam_scores.csv<\/code> contains data about students with columns: <code>StudentID<\/code>, <code>Name<\/code>, <code>Subject<\/code>, <code>Marks<\/code>, <code>Attendance_Percentage<\/code>.<\/strong><\/p>\n\n\n\n<p><strong>18. Write the code to load this CSV into a DataFrame and display the records of students who have less than 75% attendance.<\/strong><\/p>\n\n\n\n<pre class=\"wp-block-code\"><code>import pandas as pd\ndf = pd.read_csv('exam_scores.csv')\nlow_attendance = df&#91;df&#91;'Attendance_Percentage'] &lt; 75]\nprint(low_attendance)\n<\/code><\/pre>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<p><strong>19. Write the code to calculate and display the average marks for each subject.<\/strong><\/p>\n\n\n\n<pre class=\"wp-block-code\"><code>avg_marks = df.groupby('Subject')&#91;'Marks'].mean()\nprint(avg_marks)\n<\/code><\/pre>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<p><strong>20. Write the code to create a bar chart visualizing the average marks for each subject calculated in the previous step.<\/strong><\/p>\n\n\n\n<pre class=\"wp-block-code\"><code>import matplotlib.pyplot as plt\navg_marks.plot(kind='bar')\nplt.title('Average Marks per Subject')\nplt.ylabel('Average Marks')\nplt.xlabel('Subject')\nplt.xticks(rotation=0) # Keeps subject names horizontal\nplt.show()\n<\/code><\/pre>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<p><strong>21. A student with StudentID &#8216;S105&#8217; had their &#8216;Maths&#8217; paper re-evaluated, and their new score is 95. Write the code to update this specific student&#8217;s mark in the DataFrame.<\/strong><\/p>\n\n\n\n<pre class=\"wp-block-code\"><code>df.loc&#91;(df&#91;'StudentID'] == 'S105') &amp; (df&#91;'Subject'] == 'Maths'), 'Marks'] = 95\n<\/code><\/pre>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<p><strong>22. How would you save the final, modified DataFrame back to a new CSV file named <code>updated_scores.csv<\/code> without the pandas index column?<\/strong><\/p>\n\n\n\n<pre class=\"wp-block-code\"><code>df.to_csv('updated_scores.csv', index=False)\n<\/code><\/pre>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<p><strong>23. Create a scatter plot to show the relationship between <code>Attendance_Percentage<\/code> and <code>Marks<\/code>.<\/strong><\/p>\n\n\n\n<pre class=\"wp-block-code\"><code>import matplotlib.pyplot as plt\nplt.scatter(df&#91;'Attendance_Percentage'], df&#91;'Marks'], alpha=0.5)\nplt.title('Attendance vs. Marks')\nplt.xlabel('Attendance (%)')\nplt.ylabel('Marks Obtained')\nplt.grid(True)\nplt.show()<\/code><\/pre>\n\n\n\n<style>\n  .py-promo-box {\n    background-color: #f8f9fa;\n    border-left: 5px solid #4B8BBE;\n    border-radius: 5px;\n    padding: 25px;\n    margin: 30px 0;\n    text-align: center;\n    font-family: sans-serif;\n    box-shadow: 0 2px 8px rgba(0,0,0,0.1);\n  }\n  .py-promo-box h3 {\n    margin-top: 0;\n    color: #333;\n    font-size: 20px;\n  }\n  .py-promo-box p {\n    color: #555;\n    font-size: 16px;\n    margin-bottom: 20px;\n  }\n  .py-promo-box .py-button {\n    display: inline-block;\n    background-color: #FFD43B;\n    color: #3D4A5D;\n    padding: 12px 25px;\n    text-decoration: none;\n    font-weight: bold;\n    border-radius: 5px;\n    transition: background-color 0.3s ease;\n  }\n  .py-promo-box .py-button:hover {\n    background-color: #fcc700;\n  }\n<\/style>\n\n<div class=\"py-promo-box\">\n  <h3>Test Your Python Code Instantly \ud83d\ude80<\/h3>\n  <p>Want to try out the code yourself? Use our free AI-based Python IDLE right in your browser\u2014no installation needed!<\/p>\n  <a href=\"https:\/\/itxperts.co.in\/PYTHON-AI-IDLE\/\" class=\"py-button\" target=\"_blank\" rel=\"noopener noreferrer\">\n    Launch Free Python IDLE\n  <\/a>\n<\/div>\n","protected":false},"excerpt":{"rendered":"<p>important questions and answers on Python, Pandas, and Matplotlib. 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