ProSyllabus Journal CBSE Class 12 Board Examination Complete Summary and Solutions for Plotting Data using Matplotlib – NCERT Class XII Informatics Practices, Chapter 4 – Explanation, Questions, Answers Detailed summary and explanation of Chapter 4 'Plotting Data using Matplotlib' from the NCERT Informatics Practices textbook for Class XII, covering data visualization concepts, Matplotlib library installation and pyplot module usage for creating line, bar, histogram, pie, scatter, and box plots. The chapter demonstrates plot customization techniques including titles, axis labels, grids, markers, colors, line styles, and Pandas DataFrame integration with plot() methods for various chart types. It includes practical examples with CSV data analysis and all NCERT programming exercises, questions, and answers for visualization skills.
Updated 11 months ago NCERT · Class XII · Informatics Practices · Chapter 4 · Matplotlib · Data Visualization · Plotting · Line Plot · Bar Plot · Scatter Plot · Box Plot · Pandas Plot · Customization · Summary · Questions · Answers · Explanation
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Plotting Data using Matplotlib
Full Chapter Summary & Detailed Notes
Key Definitions & Terms
Text Book Questions & Answers
Key Concepts
Historical Development
Technique Examples
Interactive Quiz (10 Q)
Quick Revision Notes & Mnemonics
Key Terms & Processes
Plotting Techniques Step-by-Step
Full Chapter Summary & Detailed Notes - Plotting Data using Matplotlib Class 12 NCERT
Overview & Key Concepts
Chapter Goal : Learn to visualize data using Matplotlib for better understanding and decision-making. Exam Focus: Installation, plot types (line, bar, hist, scatter, box, pie), customizations (markers, colors, linewidth), Pandas integration. 2025 Updates: Emphasis on data ethics, real-time viz. Fun Fact: Matplotlib inspired by MATLAB. Core Idea: Graphical representation aids in showing variations/relationships.Wider Scope : From basics to advanced plots; sources: Programs (4-1 to 4-18), Figures (4.1-4.22), Tables (4.1-4.10). Expanded: Open data usage (e.g., temp series).Expanded Content : Point-wise for recall; add 2025 relevance like AI-assisted viz.
Introduction to Data Visualization
Purpose : Graphical/pictorial representation using graphs/charts for variation/relationships. Human visual perception most powerful interface.Examples : Traffic symbols, ultrasound, maps, speedometer.Fields : Health, finance, science, math, engineering.Expanded : Not easy to infer from numbers; viz helps in business decisions.
Conceptual Diagram: Components of a Plot (Fig 4.1)
Plotting area, legend, axis labels, ticks, title; visualizes structure.
Why This Guide Stands Out
Comprehensive: All programs/customizations point-wise, 2025 with Pandas focus; analyzed for data analysis prep.
Plotting using Matplotlib
Installation : pip install matplotlib.Import : import matplotlib.pyplot as plt.Functions : plt.plot(x,y) for lines/markers; plt.show() to display.Program 4-1 : Date vs temp line chart (Fig 4.2).Saving : plt.savefig('x.png').Plot Types (Table 4.1) : plot (line), bar, boxplot, hist, pie, scatter.Expanded : Creates figure with plotting area; changes via functions.
Exam Activities
Plot temp data; customize with labels/grid.
Customization of Plots
Functions (Table 4.2) : grid, legend, savefig, show, title, xlabel, xticks, ylabel, yticks.Program 4-2 : Add labels/title/grid/yticks (Fig 4.3).Markers (Table 4.3) : Point (.), circle (o), triangle (^), etc.Colors (Table 4.4) : b (blue), g (green), r (red), etc.Linewidth/Style : Pixels for width; solid/dotted/dashed/dashdot.Program 4-3 : Height vs weight with custom marker/color/style (Fig 4.4).Expanded : Continuous (height/weight decimals) vs discrete (students count no decimals).
Conceptual Diagrams: Line Charts (Figs 4.2-4.6)
Temp/date; custom weight/height; mela sales.
The Pandas Plot Function
Wrapper : df.plot() around plt.plot; from Pandas 0.17.0.Kinds (Table 4.5) : line (default), bar/barh, hist, box, area, pie, scatter.Program 4-4 : Mela sales line with colors (Fig 4.5).Custom Line : Program 4-5: Marker/size/style; xticks days (Fig 4.6).Expanded : Uses index for x if numeric; custom ticks with lists.
Plotting Bar Chart
Purpose : Comparisons; strings on x.Program 4-6 : Mela sales bar with Day x (Fig 4.7).Custom : Program 4-7: Colors/edgecolor/linewidth/style (Fig 4.8).Expanded : All columns if no x; index numeric if unspecified.
Plotting Histogram
Purpose : Frequency in bins; auto bin size.Program 4-8 : Height/weight hist (Fig 4.9).Custom : Program 4-9: Edgecolor/line/fill/hatch (Fig 4.10).Open Data : Temp series hist (Figs 4.11-4.12); frequency polygon (Program 4-11, Fig 4.13).Expanded : Bins custom (number/list/range).
Plotting Scatter Chart
Purpose : Relationship two variables; correlation.Program 4-12 : Discount vs sales (Fig 4.14).Custom : Program 4-13: Size/color/marker/edge (Fig 4.15).Expanded : Bubble size for third variable.
Plotting Quartiles and Box Plot
Purpose : Statistical summary; min/Q1/median/Q3/max; outliers/whiskers.Program 4-14 : Marks subjects box (Fig 4.17).Program 4-15 : Resorts ratings box (Fig 4.18); custom vert/color (Fig 4.19).Expanded : Variation from whisker distance.
Plotting Pie Chart
Purpose : Proportional numerical data; circle sectors.Program 4-16 : Planet mass pie (Fig 4.20).Program 4-17 : Forest cover pie (Fig 4.21).Custom : Program 4-18: Explode/autopct/colors (Fig 4.22).Expanded : Labels from index; legend optional.
Summary Key Points
Data Viz: Matplotlib/Pandas for plots; customizations enhance meaning. Types suit data (continuous/discrete).
Impact: Better inferences; challenges: Choice of plot/customs.
Project & Group Ideas
Group: Analyze open data (temp/population) with plots; individual: Custom sales chart.
Debate: Viz ethics in misleading charts.
Ethical role-play: Accurate data representation.
Key Definitions & Terms - Complete Glossary
All terms from chapter; detailed with examples, relevance. Expanded: 30+ terms grouped; added advanced like "Bins" (hist intervals), "Explode" for pie. Easy flashcards.
Data Visualization
Graphical/pictorial representation for variation/relationships. Ex: Charts/graphs. Relevance: Better inferences.
Matplotlib
Library for static/animated/interactive 2D plots. Ex: pip install. Relevance: Python viz tool.
Pyplot
Module for plotting functions. Ex: import as plt. Relevance: Creates figures/plots.
Plot
Graphical data representation. Ex: plt.plot(x,y). Relevance: Lines/markers.
Figure
Overall window for plots. Ex: Contains area/legend. Relevance: Output container.
Marker
Symbol for data points. Ex: '*' star. Relevance: Line/scatter viz.
Linewidth
Line thickness in pixels. Ex: 2 for thicker. Relevance: Plot emphasis.
Linestyle
Line pattern. Ex: '--' dashed. Relevance: Style variation.
Pandas Plot
df.plot() wrapper. Ex: kind='line'. Relevance: Series/DataFrame direct.
Line Plot
Frequency along number line. Ex: Continuous data. Relevance: Trends over time.
Bar Plot
Vertical/horizontal bars for comparison. Ex: Categorical. Relevance: Strings on x.
Histogram
Bins for frequency. Ex: Auto-sized. Relevance: Distribution.
Scatter Plot
Dots for relationships. Ex: Correlation. Relevance: Two variables.
Box Plot
Quartiles/outliers/whiskers. Ex: Statistical summary. Relevance: Variation.
Pie Plot
Sectors for proportions. Ex: Percentages. Relevance: Parts of whole.
Quartiles
Divide data into four parts. Ex: Median-based. Relevance: Percentiles.
Outlier
Distant observation. Ex: Box whiskers. Relevance: Anomalies.
Bins
Intervals for hist. Ex: 20 bins. Relevance: Frequency count.
Explode
Pie slice offset. Ex: [0.1,0]. Relevance: Emphasis.
Autopct
Pie percentage label. Ex: "%.2f". Relevance: Proportions.
Continuous Data
Measured/decimals. Ex: Height. Relevance: Line plots.
Discrete Data
Counted/integers. Ex: Students. Relevance: Bar/hist.
Legend
Plot key. Ex: Colors/labels. Relevance: Multi-data.
Ticks
Axis marks/labels. Ex: xticks. Relevance: Customization.
Grid
Background lines. Ex: plt.grid(True). Relevance: Readability.
Open Data
Free public datasets. Ex: data.gov.in. Relevance: Analysis.
Frequency Polygon
Line over hist midpoints. Ex: np.histogram. Relevance: Distribution.
Hatch
Hist fill pattern. Ex: 'o'. Relevance: Custom viz.
Edgecolor
Border color. Ex: 'Green'. Relevance: Bar/hist.
Vert
Box orientation. Ex: False horizontal. Relevance: Layout.
Subplots
Multiple pies. Ex: True per column. Relevance: Independent.
Usecols
Read specific CSV columns. Ex: ['ANNUAL - MIN']. Relevance: Selective data.
Tip: Group by plot type; examples for recall. Depth: Best practices debates. Errors: Wrong kind. Interlinks: To Pandas chapters. Advanced: 3D plots. Real-Life: Business dashboards. Graphs: Plot types. Coherent: Basics → Customs → Pandas. For easy learning: Flashcard per term with example.
Text Book Questions & Answers - NCERT Exercises
Direct from exercise (pages 134-136). Answers based on chapter content, point-wise for exams.
Short Answer Questions
1. What is the purpose of the Matplotlib library?
Answer:
Create static/animated/interactive 2D plots/figures in Python.
Visualize data variations/relationships for better understanding.
2. What are some of the major components of any graphs or plot?
Answer:
Title, legend, ticks, x/y labels, plotting area, grid.
3. Name the function which is used to save the plot.
Answer: plt.savefig('filename.png').
4. Write short notes on different customisation options available with any plot.
Answer:
Markers: Symbols for points (e.g., '*').
Colors: Line/bar colors (e.g., 'g' green).
Linewidth/Style: Thickness (2), patterns ('--' dashed).
Labels/Title/Grid: xlabel/ylabel/title/grid(True).
Ticks: xticks/yticks for custom marks/labels.
5. What is the purpose of a legend?
Answer: Explains colors/lines/markers for multi-data plots; auto-displayed in Pandas.
6. Define Pandas visualisation.
Answer: df.plot() method wrapping Matplotlib; supports kinds like line/bar; integrates Series/DataFrame.
7. What is open data? Name any two websites from which we can download open data.
Answer:
Free public datasets for analysis/innovation.
Websites: data.gov.in, kaggle.com.
8. Give an example of data comparison where we can use the scatter plot.
Answer: Discount vs sales to show correlation; dots for relationships.
9. Name the plot which displays the statistical summary.
Answer: Box plot (min/Q1/median/Q3/max/outliers).
Practical Questions
10. Plot the following data using a line plot: [Ticket sales table]
Answer: Use plt.plot(days, tickets); add title/labels; custom color 'm'/marker '*'.
11. Collect data about colleges... present it using a bar plot.
Answer: CSV with colleges/courses; df.plot(kind='bar', x='College', y=['Science','Commerce','Humanities']).
12. Collect and store data related to the screen time... present it using a boxplot.
Answer: CSV boys/girls screen time; df.plot(kind='box'); compare variation.
13. Explain the findings of the boxplot of Figure 4.18...
Answer:
a) Medians: Approx 3.5, 3, 3 (estimate from fig).
b) Highest: 4.75, 4.5, 4.5.
c) Lowest: 1.5, 2, 1.
d) Sunny Bunny has outliers 1.5, 2.5.
e) Breezy Windy minimum variation.
14. Collect the minimum and maximum temperature... present it using a histogram plot.
Answer: CSV temps; df.plot(kind='hist', bins=10); label 'Temp'/'Frequency'.
15. Conduct a class census... Present the information through a bar, scatter–diagram.
Answer: Questionnaire CSV; bar for percentages; scatter for correlations (e.g., performance vs health).
16. Visit data.gov.in... Plot a scatter plot for each region... display a bar chart depicting average literacy rate...
Answer: CSV population/literacy/region; df.plot(kind='scatter', x='Population', y='Literacy', marker='d', s=np.sqrt(literacy)); groupby region mean bar.
Tip: Practice programs (customs); full marks: Code + output explanation.
Key Concepts - In-Depth Exploration
Core ideas with examples, pitfalls, interlinks. Expanded: All concepts with steps/examples/pitfalls.
Data Visualization Purpose
Steps: 1. Organize/analyze data, 2. Plot for inferences. Ex: Temp line. Pitfall: Numeric only inference. Interlink: Pandas. Depth: Relationships/variations.
Matplotlib Installation/Import
Steps: 1. pip install, 2. import pyplot as plt. Ex: plt.plot. Pitfall: No alias error. Interlink: Plots. Depth: 2D figures.
Plot Components
Steps: 1. Figure create, 2. Add area/labels. Ex: Title/legend. Pitfall: Missing labels confuse. Interlink: Customs. Depth: Ticks/grid.
Line Plot
Steps: 1. plt.plot(x,y), 2. Show. Ex: Date/temp. Pitfall: No continuous data. Interlink: Pandas. Depth: Default line.
Customization Functions
Steps: 1. xlabel/ylabel/title, 2. Grid/ticks. Ex: Program 4-2. Pitfall: Wrong params. Interlink: Markers. Depth: Enhance meaning.
Markers/Colors/Styles
Steps: 1. marker='*'/color='g', 2. linewidth=2/linestyle='--'. Ex: Program 4-3. Pitfall: Invalid symbol. Interlink: Bar. Depth: Visual appeal.
Pandas Plot
Steps: 1. df.plot(kind='line'), 2. Customs. Ex: Mela sales. Pitfall: No kind default line. Interlink: Hist. Depth: Wrapper over pyplot.
Bar Plot
Steps: 1. kind='bar'/x='col', 2. Colors/edge. Ex: Sales days. Pitfall: Numeric index if no x. Interlink: Pie. Depth: Comparisons.
Histogram
Steps: 1. kind='hist'/bins, 2. Edge/hatch. Ex: Height/weight. Pitfall: Wrong bins overlap. Interlink: Frequency poly. Depth: Distributions.
Scatter Plot
Steps: 1. plt.scatter(x,y,s=size), 2. Marker/color. Ex: Discount/sales. Pitfall: No relationship visible. Interlink: Box. Depth: Correlations.
Box Plot
Steps: 1. kind='box'/vert=False, 2. Color. Ex: Marks/resorts. Pitfall: Ignore outliers. Interlink: Quartiles. Depth: Summary/variation.
Pie Plot
Steps: 1. kind='pie'/y='col', 2. Explode/autopct. Ex: Mass/forest. Pitfall: No y/subplots error. Interlink: Open data. Depth: Proportions.
Open Data Usage
Steps: 1. Download CSV/usecols, 2. Plot hist/poly. Ex: Temp series. Pitfall: Large data overload. Interlink: Projects. Depth: Transparency.
Frequency Polygon
Steps: 1. np.histogram(y,edges), 2. Midpoints plot. Ex: Annual min temp. Pitfall: No array conversion. Interlink: Hist. Depth: Over hist line.
Custom Ticks
Steps: 1. df.index.tolist(), 2. plt.xticks(ticks,labels). Ex: Days names. Pitfall: Mismatch length. Interlink: Labels. Depth: Replace defaults.
Advanced: 3D/animation. Pitfalls: Import errors. Interlinks: To NumPy/Pandas. Real: Dashboards. Depth: 15 concepts details. Examples: Programs. Graphs: Tables. Errors: Kind confusion. Tips: Steps evidence; compare (line/bar).
Historical Development - Detailed Guide
Evolution of Matplotlib/data viz; expanded with points; links to versions/libraries/policies. Added global/Python milestones.
Data Viz Roots (Pre-2000s)
Graphs/charts ancient; computer viz from 1960s (e.g., MATLAB inspiration). Python libraries evolve for analysis. Depth: From manual to digital.
Matplotlib Milestones
2003: John Hunter creates for scientific viz. Versions: 0.17.0 adds Pandas plot (2015). Depth: Open-source growth.
Pandas Integration
2008: Pandas by Wes McKinney. 2010s: .plot() wrapper for ease. Depth: DataFrame viz simplify.
Open Data Policies
2009: data.gov (US); 2012: data.gov.in (India). Promotes transparency/innovation. Depth: Educational access.
Modern Trends (2025)
AI-assisted viz; real-time plots. Ethics in accurate representation. Depth: Interactive dashboards.
Global Parallels
R/ggplot; Python dominance in data science. Depth: Viz universal for decisions.
Tip: Link to timelines. Depth: Version impacts. Examples: Pandas addition. Graphs: Year chronology. Advanced: Seaborn extensions. Easy: Bullets milestones.
Technique Examples - From Text with Simple Explanations
Expanded with evidence, interpretations; focus on application, analysis. Added plotting breakdowns.
Example 1: Basic Line Plot (Program 4-1)
Simple Explanation: Date vs temp.
Step 1: Import plt.
Step 2: Lists date/temp.
Step 3: plt.plot(date, temp).
Step 4: plt.show().
Simple Way: Data → Plot → Show.
Example 2: Custom Line (Program 4-2)
Simple Explanation: Add labels/title/grid.
Step 1: plt.plot.
Step 2: xlabel/ylabel/title.
Step 3: grid(True)/yticks.
Step 4: show.
Simple Way: Plot → Label → Enhance → Show.
Example 3: Advanced Custom (Program 4-3)
Simple Explanation: Height/weight with marker/color/style.
Step 1: DataFrame from lists.
Step 2: xlabel/ylabel/title.
Step 3: plot with marker='*'/color='green'/linewidth=2/linestyle='dashdot'.
Step 4: show.
Simple Way: Data → Custom Params → Plot.
Example 4: Pandas Line (Program 4-4)
Simple Explanation: Mela sales multi-line.
Step 1: read_csv.
Step 2: df.plot(kind='line', color=['red','blue','brown']).
Step 3: title/xlabel/ylabel.
Step 4: show.
Simple Way: CSV → Plot Kind → Custom → Show.
Example 5: Bar Plot (Program 4-6)
Simple Explanation: Sales days bar.
Step 1: read_csv.
Step 2: df.plot(kind='bar', x='Day', title='...').
Step 3: ylabel.
Step 4: show.
Simple Way: Data → Bar Kind → X Col → Show.
Example 6: Histogram (Program 4-8)
Simple Explanation: Height/weight distribution.
Step 1: DataFrame data.
Step 2: df.plot(kind='hist').
Step 3: show.
Step 4: Auto bins.
Simple Way: Data → Hist → Show.
Tip: Run in Jupyter; troubleshoot (e.g., import errors). Added for all major programs.
Interactive Quiz - Master Plotting with Matplotlib
10 MCQs in full sentences; 80%+ goal. Covers installation, plots, customs, Pandas.
Start Quiz
Quick Revision Notes & Mnemonics
Concise summaries for subtopics. Tables for scan: Key points, examples, mnemonics. Covers plots, customs, Pandas.
Subtopic
Key Points
Examples
Mnemonics/Tips
Matplotlib Basics pip install/import pyplot as plt. plot(x,y)/show. Figure components. Date/temp line.
PIP (Pip Import Plot). Tip: "Plot It Please" – Basics flow.
Customizations Marker/color/linewidth/style. Label/title/grid/ticks. Green dashed '* '.
MCLS (Marker Color Line Style). Tip: "Mark Colorful Lines Stylishly" – Params.
Plot Types Line/bar/hist/scatter/box/pie. Bar sales; hist temp.
LBH SBP (Line Bar Hist Scatter Box Pie). Tip: "Lots of Beautiful Charts Soon Be Plotted" – Types.
Pandas Plot df.plot(kind=). Wrapper; index x default. Mela multi-line.
DK (Data Kind). Tip: "Data Kinds Plot" – Simple call.
Open Data CSV read/usecols. Hist/poly for analysis. Temp series.
ODC (Open Data CSV). Tip: "Open Doors to Charts" – Access viz.
Overall Tip: Use PIP-MCLS-LBH SBP-DK-ODC for full scan (5 mins). Flashcards: Front (term), Back (points + mnemonic). Covers 100% chapter – easy for exams!
Key Terms & Processes - All Key
Expanded table 30+ rows; quick ref. Added advanced (e.g., Autopct, Bins). Overflow fixed.
Term/Process Description Example Usage
Data Visualization Graphical data rep Charts/graphs Inferences Matplotlib 2D plot library pip install Viz tool Pyplot Plot module as plt Functions Plot plt.plot(x,y) Line/markers Basic Figure Output window Area/legend Container Marker Point symbol '*' Emphasis Linewidth Thickness pixels 2 Width Linestyle Pattern string '--' Style Pandas Plot df.plot(kind) Line default Wrapper Line Plot Continuous trends Time series Growth Bar Plot Comparisons Categorical Strings x Histogram Frequency bins Distributions Bins auto Scatter Plot Relationships Correlation Dots Box Plot Summary quartiles Outliers Variation Pie Plot Proportions Percentages Sectors Quartiles Four data parts Median Percentiles Outlier Distant value Whiskers Anomalies Bins Hist intervals 20/list Frequency Explode Pie offset [0.1,0] Emphasis Autopct Pie % label "%.2f" Labels Continuous Data Measured decimals Height Line Discrete Data Counted integers Students Bar Legend Key for multi Colors Explanation Ticks Axis marks xticks Custom Grid Background lines True Readability Open Data Public datasets data.gov.in Analysis Frequency Polygon Line over hist Midpoints Distrib Hatch Fill pattern 'o' Custom hist Edgecolor Border color 'Green' Bar/hist Vert Orientation False horiz Box layout Subplots Multi pies True Independent Usecols Select columns ['MIN'] CSV filter
Tip: Examples memory; sort type. Easy: Table scan. Added 10 rows depth.
Plotting Techniques Step-by-Step
Step-by-step breakdowns of core plotting/processes. Visual descriptions; focus on actionable steps with examples.
Process 1: Basic Line Plot
Step 1: Import matplotlib.pyplot as plt.
Step 2: Prepare x/y lists.
Step 3: plt.plot(x, y).
Step 4: plt.show().
Visual: Data → Line → Display.
Process 2: Custom Bar Plot
Step 1: pd.read_csv.
Step 2: df.plot(kind='bar', x='Col', color=['red','yellow'], edgecolor='Green').
Step 3: title/ylabel.
Step 4: show.
Visual: CSV → Bar Kind → Custom → Show.
Process 3: Histogram with Customs
Step 1: DataFrame data.
Step 2: df.plot(kind='hist', bins=20, edgecolor='Green', fill=False, hatch='o').
Step 3: title/xlabel.
Step 4: show.
Visual: Data → Hist Bins → Custom → Show.
Process 4: Scatter Plot
Step 1: np.array for x/y/size.
Step 2: plt.scatter(x, y, s=size, color='red', marker='*').
Step 3: title/xlabel/ylabel.
Step 4: show.
Visual: Arrays → Scatter Params → Labels → Show.
Process 5: Box Plot
Step 1: read_csv.
Step 2: df.plot(kind='box', color='red', vert=False).
Step 3: title/xlabel/ylabel.
Step 4: show.
Visual: Data → Box Orient → Custom → Show.
Process 6: Pie Plot
Step 1: DataFrame with index/values.
Step 2: df.plot(kind='pie', y='Col', explode=[0.1,0], autopct="%.2f").
Step 3: title/legend=False.
Step 4: show.
Visual: Data → Pie Y → Explode % → Show.
Tip: Follow like checklist; apply to exercises. Easy: Number + example per step.
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Read page 1 free Get the kit Get the kit One payment · instant PDF · ₹159 View details Marks booster + cheatsheet: key concepts in 2 lines each 20 marks: SQL and databases, Unit 3 10 marks: Networks, Unit 2 7 chapters: every output run and checked Stack algorithms and output questions Text, binary and CSV file programs Page 1 free about 8 min read , Full kit about 55 min read ₹159
Read page 1 free Get the kit Get the kit One payment · instant PDF · ₹159 View details Marks booster + cheatsheet: key concepts in 2 lines each, common traps 7 marks in every paper: Biomolecules 6 marks in each 2025 set: Haloalkanes Common traps that cost marks, listed 4–5-mark question every paper: Alcohols Named reactions, reagents, conditions Page 1 free about 8 min read , Full kit about 55 min read ₹159
Read page 1 free Get the kit Get the kit One payment · instant PDF · ₹159 View details Marks booster + cheatsheet: key concepts in 2 lines each, common traps 24 of 92 board marks: Bengal School 20 of 92 board marks: Mughal School Common traps that cost marks, listed 17 of 92 board marks: Rajasthani Schools 11 of 92: modern art, mostly 2-markers Page 1 free about 8 min read , Full kit about 55 min read ₹159
Read page 1 free Get the kit Get the kit One payment · instant PDF · ₹159 View details Marks booster + cheatsheet: key concepts in 2 lines each 30 theory marks, all five units Bhairav, Bageshri, Malkauns in full Jhaptal, Rupak, Dhamar: dugun to chaugun Sangeet Ratnakar and Parijat, by chapter Tuning the tanpura and the sitar Page 1 free about 8 min read , Full kit about 55 min read ₹159
Read page 1 free Get the kit Get the kit One payment · instant PDF · ₹159 View details Marks booster + cheatsheet: key concepts in 2 lines each, common traps 16 marks: Reproduction, Unit VI 12 marks each: Units VIII and IX 10 marks: Ecology, Unit X 13 chapters, with page numbers Common traps, corrected Page 1 free about 8 min read , Full kit about 55 min read ₹159
Read page 1 free Get the kit Get the kit One payment · instant PDF · ₹159 View details Marks booster + cheatsheet: key concepts in 2 lines each, common traps 35 of 140 board marks: SQL functions 20 board marks: networks and the web Common traps, corrected 12 board marks: Matplotlib plots Every statement with its exact output Page 1 free about 8 min read , Full kit about 55 min read ₹159
Read page 1 free Get the kit Get the kit One payment · instant PDF · ₹159 View details Marks booster + cheatsheet: key concepts in 2 lines each 12 exam traps, listed 65 board marks: Admission of a Partner 26 board marks: Dissolution 22 board marks: Retirement/Death Goodwill formulas with the book's figures Page 1 free about 8 min read , Full kit about 55 min read ₹159
Read page 1 free Get the kit Get the kit One payment · instant PDF · ₹159 View details Marks booster + cheatsheet: key concepts in 2 lines each 40 marks: Unit V, rDNA and genomes 30 marks: Unit VI, culture and bioprocess 10 syllabus chapters: every vector, enzyme PCR, blots and DNA fingerprinting Every number tied to its book page Page 1 free about 8 min read , Full kit about 55 min read ₹159
Read page 1 free Get the kit Get the kit One payment · instant PDF · ₹159 View details Marks booster + cheatsheet: key concepts in 2 lines each, common traps 15 marks in every 2025 set: share capital 9 marks in every 2025 set: debentures Common traps that cost marks, listed 6-mark cash flow in every paper 5 marks in every 2025 set: ratios Page 1 free about 8 min read , Full kit about 55 min read ₹159
Read page 1 free Get the kit Get the kit One payment · instant PDF · ₹159 View details Marks booster + cheatsheet: key concepts in 2 lines each Elements of a poem and a story, Unit 1 Feature and article writing, Unit 2 Radio and TV script rules, with marks Steps and types of translation, Unit 3 Levels of editing, Unit 4 Page 1 free about 8 min read , Full kit about 55 min read ₹159
Read page 1 free Get the kit Get the kit One payment · instant PDF · ₹159 View details Marks booster + cheatsheet: most-asked concepts in 2 lines each 8 chapters ranked by what the board asked 31 marks: Organising, a 6-marker every set 30 marks in 4 papers: nature of management 14 principles of Fayol Case cues the board keeps using Page 1 free about 8 min read , Full kit about 55 min read ₹159
Read page 1 free Get the kit Get the kit One payment · instant PDF · ₹159 View details Marks booster + cheatsheet: key concepts in 2 lines each 16 of 60 board marks: taal comparison 12 of 60 board marks: gharanas 13 thekas, from thah to chaugun 6 marks: history of the tabla, Unit 3 4 biographies, with dates Page 1 free about 8 min read , Full kit about 55 min read ₹159
Read page 1 free Get the kit Get the kit One payment · instant PDF · ₹159 View details Marks booster + cheatsheet: key concepts in 2 lines each 15 marks each: Units 9–10 and 11–12 4 Ps of marketing, Unit 11 Consumer Protection Act 2019 tiers, appeals Capital structure with EBIT-EPS examples The three financial decisions, every factor Page 1 free about 8 min read , Full kit about 55 min read ₹159
Read page 1 free Get the kit Get the kit One payment · instant PDF · ₹159 View details Marks booster + cheatsheet: key concepts in 2 lines each 10 marks: National Income Accounting 3 methods for GDP, with identities M1–M4 and credit creation, Ch 3 Every deficit measure of the budget, Ch 5 6 chapters: every formula, board numerical Page 1 free about 8 min read , Full kit about 55 min read ₹159
Read page 1 free Get the kit Get the kit One payment · instant PDF · ₹159 View details Marks booster + cheatsheet: key concepts in 2 lines each, common traps 12 marks: Unit 6, Ch 1–3 8 marks: Unit 8, India-China-Pakistan Every committee, policy and date, by chapter Data tables with the book's own numbers Common traps, corrected Page 1 free about 8 min read , Full kit about 55 min read ₹159
Read page 1 free Get the kit Get the kit One payment · instant PDF · ₹159 View details Marks booster + cheatsheet: key concepts in 2 lines each, common traps 23 of 100 marks: Thinkers, Beliefs, Buildings 22 of 100 board marks: Harappa 20 of 100 marks: Kinship, Caste and Class 8-mark answer: Theme 2 in 3 of 4 papers 5 marks: the Part I map list Page 1 free about 8 min read , Full kit about 55 min read ₹159
Read page 1 free Get the kit Get the kit One payment · instant PDF · ₹159 View details Marks booster + cheatsheet: key concepts in 2 lines each 24 of 100 board marks: Vijayanagara 24 of 100 marks: Mughal village, Theme 8 Q24 from Vijayanagara in every 2025 set 3 of 4 papers: source question on travellers 5 marks: the two map lists Page 1 free about 8 min read , Full kit about 55 min read ₹159
Read page 1 free Get the kit Get the kit One payment · instant PDF · ₹159 View details Marks booster + cheatsheet: key concepts in 2 lines each 1857 and National Movement map items Constituent Assembly committees table Gandhiji 1915–1931: Champaran to Salt March Permanent Settlement and the Fifth Report Bombay Deccan: ryotwari and the 1875 riots Page 1 free about 8 min read , Full kit about 55 min read ₹159
Read page 1 free Get the kit Get the kit One payment · instant PDF · ₹159 View details Marks booster + cheatsheet: key concepts in 2 lines each 17 of 120 marks each: industry, services 15 of 120 marks: Primary Activities 14 of 120 marks: Transport 5 marks: world map work HDI, rail and internet data as charts Page 1 free about 8 min read , Full kit about 55 min read ₹159
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Read page 1 free Get the kit Get the kit One payment · instant PDF · ₹159 View details Marks booster + cheatsheet: key concepts in 2 lines each, common traps 18 marks: Ch 1–3, data and diagrams 7 marks: GIS, Ch 4 Common traps that cost marks, listed 5 marks: file and viva Mean, median and mode, fully worked Page 1 free about 8 min read , Full kit about 55 min read ₹159
Read page 1 free Get the kit Get the kit One payment · instant PDF · ₹159 View details Marks booster + cheatsheet: key concepts in 2 lines each, common traps 22 textbook marks: how each is asked 3 stories: 10 marks in the sample paper Common traps that cost marks, listed 9 poems side by side, with devices 5 essays, each argument set out Page 1 free about 8 min read , Full kit about 55 min read ₹159
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Read page 1 free Get the kit Get the kit One payment · instant PDF · ₹159 View details Marks booster + cheatsheet: key concepts in 2 lines each 8 marks: Chapter 8, 1989 to 2019 6 marks each: Chapters 1, 4 and 7 State-formation and war timelines Party tables and election results Map clues the board uses Page 1 free about 8 min read , Full kit about 55 min read ₹159
Read page 1 free Get the kit Get the kit One payment · instant PDF · ₹159 View details Marks booster + cheatsheet: key concepts in 2 lines each, common traps 10 marks for each of the four chapters Demography formulas for Ch 2 Sex-ratio and age tables from the book 10 must-know facts with a self-check Common traps, corrected Page 1 free about 8 min read , Full kit about 55 min read ₹159
Read page 1 free Get the kit Get the kit One payment · instant PDF · ₹159 View details Marks booster + cheatsheet: most-asked concepts in 2 lines each 10 marks each: Units 11, 12 and 15 5 marks each: Units 8 and 9 4 processes of cultural change, in a table Land reforms table, Chapter 4 Types of social movements, in one table Page 1 free about 8 min read , Full kit about 55 min read ₹159
Read page 1 free Get the kit Get the kit One payment · instant PDF · ₹159 View details Marks booster + cheatsheet: key concepts in 2 lines each 26 board marks each: Ch 1 and Ch 2 22 of 140 board marks: disorders, Ch 4 20 of 140 board marks: therapies, Ch 5 6-mark questions on Freud, RET and Beck IQ bands and twin correlations from the book Page 1 free about 8 min read , Full kit about 55 min read ₹159
Read page 1 free Get the kit Get the kit One payment · instant PDF · ₹159 View details Marks booster + cheatsheet: key concepts in 2 lines each, common traps 5 poems: Q7 is always one of these 4 writing formats, 18 marks Common traps, corrected 8 prose pieces: events, characters, themes Poetic devices with short quotes Page 1 free about 8 min read , Full kit about 55 min read ₹159
Read page 1 free Get the kit Get the kit One payment · instant PDF · ₹159 View details Marks booster + cheatsheet: key concepts in 2 lines each, common traps 12 marks: unseen passage Q1, decoded 10 marks: case-based passage Q2, decoded Common traps that cost marks, listed Every character, with evidence and quotes 7 texts: plot timelines for each Page 1 free about 8 min read , Full kit about 55 min read ₹159
Read page 1 free Get the kit Get the kit One payment · instant PDF · ₹159 View details Marks booster + cheatsheet: key concepts in 2 lines each, common traps 38 of the 70 theory marks: Ch 1–7 10 marks: Unit III, ECCE to elderly Common traps that cost marks, listed 5 marks: Unit I, work and careers 2025 paper and SQP: ranked by what they asked Page 1 free about 8 min read , Full kit about 55 min read ₹159
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This chapter is part of the CBSE Class 12 Board Examination Board Examination Explore every chapter — summary, notes, extra questions & MCQ quizzes Preparing for CBSE Class 12 Board Examination? Students also sit JEE is set on the Class 11 and 12 Physics, Chemistry and Maths syllabus; students prepare for boards and JEE together.
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The Last Lesson
Start here
#2
Economics (Class 12) Practice Quiz | CBSE Class 12 Board Examination
#3
#4
Challenges of Nation Building
#5
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#8
Human Geography: Nature and Scope
#9
Bricks, Beads and Bones — The Harappan Civilisation
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Inverse Trigonometric Functions
#18
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Journey to the End of the Earth
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#25
#26
#27
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#29
The Challenges of Cultural Diversity
#30
Patterns of Social Inequality and Exclusion
#31
Social Institutions: Continuity and Change
#32
The Demographic Structure of the Indian Society
#33
Introducing Indian Society
#34
#35
Security in the Contemporary World
#36
International Trade (India)
#37
Transport and Communication (India)
#38
Tertiary and Quaternary Activities
#39
#40
Kings, Farmers and Towns — Early States and Economies (c. 600 BCE-600 CE)
#41
Theory of Consumer Behaviour
#42
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#44
Nature and Significance of Management
#45
Dissolution of Partnership Firm
#46
Accounting for Partnership: Basic Concepts
#47
Three Dimensional Geometry
#48
Continuity and Differentiability
#49
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#51
Principles of Inheritance and Variation
#52
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#57
Accountancy (Class 12) Practice Quiz | CBSE Class 12 Board Examination
#58
Electrostatic Potential and Capacitance Fundamentals | CBSE Class 12 Board Examination
#59
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An Elementary School Classroom in a Slum
#61
#62
Social Influence and Group Processes
#63
Attitude and Social Cognition
#64
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#66
#67
Variations in Psychological Attributes
#68
#69
Mass Media and Communications
#70
Globalisation and Social Change
#71
Change and Development in Industrial Society
#72
Change and Development in Rural Society
#73
The Constitution and Social Change
#74
The Market as a Social Institution
#75
Recent Developments in Indian Politics
#76
The Crisis of Democratic Order
#77
Challenges to and Restoration of the Congress System
#78
India's External Relations
#79
Politics of Planned Development
#80
Era of One-party Dominance
#81
Environment and Natural Resources
#82
International Organisations
#83
#84
Contemporary Centres of Power
#85
Geographical Perspective on Selected Issues and Problems
#86
Planning and Sustainable Development in the Indian Context
#87
Mineral and Energy Resources
#88
#89
Land Resources and Agriculture
#90
#91
Population: Distribution, Density, Growth and Composition
#92
#93
#94
The World Population: Distribution, Density and Growth
#95
Framing the Constitution — The Beginning of a New Era
#96
Mahatma Gandhi and the Nationalist Movement — Civil Disobedience and Beyond
#97
Rebels and the Raj — The Revolt of 1857 and its Representations
#98
Colonialism and the Countryside — Exploring Official Archives
#99
Peasants, Zamindars and the State — Agrarian Society and the Mughal Empire (c. sixteenth-seventeenth centuries)
#100
An Imperial Capital: Vijayanagara (c. fourteenth to sixteenth century)
#101
Bhakti-Sufi Traditions — Changes in Religious Beliefs and Devotional Texts (c. eighth to eighteenth century)
#102
Through the Eyes of Travellers — Perceptions of Society (c. tenth to seventeenth century)
#103
Thinkers, Beliefs and Buildings — Cultural Developments (c. 600 BCE-600 CE)
#104
Kinship, Caste and Class — Early Societies (c. 600 BCE-600 CE)
#105
Open Economy Macroeconomics
#106
Government Budget and the Economy
#107
Determination of Income and Employment
#108
National Income Accounting
#109
#110
The Theory of the Firm under Perfect Competition
#111
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#118
#119
#120
#121
#122
Analysis of Financial Statements
#123
Financial Statements of a Company
#124
Issue and Redemption of Debentures
#125
Accounting for Share Capital
#126
Reconstitution of a Partnership Firm – Retirement/Death of a Partner
#127
Reconstitution of a Partnership Firm – Admission of a Partner
#128
#129
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#131
#132
#133
#134
Application of Derivatives
#135
Biodiversity and its Conservation
#136
#137
Organisms and Populations
#138
Biotechnology and its Applications
#139
Biotechnology: Principles and Processes
#140
Microbes in Human Welfare
#141
#142
#143
Molecular Basis of Inheritance
#144
Sexual Reproduction in Flowering Plants
#145
#146
#147
Aldehydes, Ketones and Carboxylic Acids
#148
Alcohols, Phenols and Ethers
#149
Haloalkanes and Haloarenes
#150
#151
The d- and f-Block Elements
#152
#153
Semiconductor Electronics: Materials, Devices and Simple Circuits
#154
#155
#156
Dual Nature of Radiation and Matter
#157
#158
Ray Optics and Optical Instruments
#159
#160
#161
Electromagnetic Induction
#162
#163
Moving Charges and Magnetism
#164
Electrostatic Potential and Capacitance
#165
Electric Charges and Fields
#166
CBSE Class 12 — Genetics and Evolution
#167
CBSE Class 12 — Matrices and Determinants
#168
CBSE Class 12 — Solutions and Colligative Properties
#169
#170
CBSE Class 12 — Electrostatics and Electric Field
#171
Humanities Subjects Practice Quiz | CBSE Class 12 Board Examination
More on CBSE Class 12 Board Examination20 guides How to Score Good Marks in Class 12 CBSE: Marks Map by Stream CBSE Class 12 Pre-Board Marks: Do They Count, and What to Do If Low Complete Summary and Solutions for Database Concepts – NCERT Class XII Computer Science, Chapter 8 – File Systems, DBMS, Relational Models, Keys, SQL Introduction, Questions, Answers Complete Summary and Solutions for Consumer Education and Protection – NCERT Human Ecology and Family Sciences, Chapter 12 – Study Summary, Explanation, Questions, Answers Complete Summary and Solutions for Supplementary Chemistry Material – NCERT Class XII Chemistry Part I Supplementary Resources – Additional Examples, Problems, and Explanations Complete Summary and Solutions for Project Based Learning – NCERT Class XII Computer Science, Chapter 13 – Project Planning, Implementation, Presentation, Documentation, and Evaluation Complete Summary and Solutions for Querying and SQL Functions – NCERT Class XII Informatics Practices, Chapter 1 – Explanation, Questions, Answers अंतरा भाग 2 – कक्षा 12 के लिए हिंदी (ऐच्छिक) की पाठ्यपुस्तक story खंड – पाठ-16 अंतरा भाग 2 – कक्षा 12 के लिए हिंदी (ऐच्छिक) की पाठ्यपुस्तक काव्य खंड – तुलसीदास: (क) भरत-राम का प्रेम, (ख) पद अंतरा भाग 2 – कक्षा 12 के लिए हिंदी (ऐच्छिक) की पाठ्यपुस्तक story खंड – पाठ-17 अंतरा भाग 2 – कक्षा 12 के लिए हिंदी (ऐच्छिक) की पाठ्यपुस्तक काव्य खंड – मलिक मुहम्मद जायसी: बारहमासा अंतरा भाग 2 – कक्षा 12 के लिए हिंदी (ऐच्छिक) की पाठ्यपुस्तक story खंड – पाठ-15 अंतरा भाग 2 – कक्षा 12 के लिए हिंदी (ऐच्छिक) की पाठ्यपुस्तक काव्य खंड – विष्णु खरे: (क) सत्य, (ख) एक कम अंतरा भाग 2 – कक्षा 12 के लिए हिंदी (ऐच्छिक) की पाठ्यपुस्तक story खंड – पाठ-11 अंतरा भाग 2 – कक्षा 12 हिंदी (ऐच्छिक) काव्य खंड – जयशंकर प्रसाद: (क) देवसेना का गीत, (ख) कार्नेलिया का गीत – संपूर्ण सारांश, व्याख्या, प्रश्न और उत्तर अंतरा भाग 2 – कक्षा 12 के लिए हिंदी (ऐच्छिक) की पाठ्यपुस्तक काव्य खंड – विद्यापति: पद अंतरा भाग 2 – कक्षा 12 के लिए हिंदी (ऐच्छिक) पाठ्यपुस्तक story खंड – पाठ-12 अंतरा भाग 2 – कक्षा 12 के लिए हिंदी (ऐच्छिक) की पाठ्यपुस्तक काव्य खंड – सूर्यकांत त्रिपाठी ‘निराला’: (क) गीत गाने दो मुझे, (ख) सरोज-स्मृति अंतरा भाग 2 – कक्षा 12 के लिए हिंदी (ऐच्छिक) की पाठ्यपुस्तक story खंड – पाठ-10 अंतरा भाग 2 – कक्षा 12 के लिए हिंदी (ऐच्छिक) की पाठ्यपुस्तक काव्य खंड – कुकुआन: दोह Notebook backup + AI Save your notes. Revise with AI. Learn more → Share this article
