Line plot
A line plot is a chart that connects ordered data values with line segments to show changes, relationships, or trends.
Pandas Workout: 200 exercises to make you a stronger data analyst
A chart that represents observations as points connected by line segments, typically to show change across an ordered dimension.
- How it is used
- Compares numeric measurements across ordered values while revealing category-specific trends through colored or separated lines.
- How deep it goes
- Demonstrates plotting, index repair, grouping, confidence intervals, and facet layout, but does not develop statistical theory.
- Examples
- Uses city weather temperatures, daily taxi distance, daily trip counts, and monthly taxi comparisons.
- What you can do after
- Build it from scratch with Seaborn by selecting axes, choosing line kind, coloring categories, aggregating values, and arranging facets.
Read how Pandas Workout: 200 exercises to make you a stronger data analyst explains line plot →
Effective Data Analysis
A chart is a visual representation of data designed to communicate patterns, comparisons, or trends.
- How it is used
- Communicates time-based performance trends and comparisons between stakeholder-relevant groups.
- How deep it goes
- Explains selection, segmentation, labeling, axis limits, and logarithmic scales, but stops short of implementation code.
- Examples
- Uses weekly sales, purchases, bounce rate, subscribers, followers, and page views in dashboard exercises.
- What you can do after
- Build it in a dashboard, choose useful groupings, label it clearly, and evaluate whether its scales communicate change responsibly.
Statistics Slam Dunk
A line chart represents values or trends across ordered positions by connecting plotted points with line segments.
- How it is used
- Visualizes change across ordered seasons, trials, streaks, or other positions.
- How deep it goes
- Explains data preparation, aesthetics, geoms, axis controls, labels, themes, and visual interpretation without deriving plotting internals.
- Examples
- Uses NBA win-share inequality, Laplace probability, and Julius Randle free-throw percentages following consecutive makes.
- What you can do after
- Apply it via ggplot2 to build, customize, and interpret ordered trends with connected points.
Everyday Data Visualization
A chart that connects plotted values with lines to show change or relationships across an ordered dimension.
- How it is used
- Guides chart selection and visual encoding for change across continuous or meaningfully ordered dimensions.
- How deep it goes
- Explains continuous-data rationale, misleading category connections, multiline alternatives, and decluttering, without implementation details.
- Examples
- Uses fruit taste scores, seasonal timing, and contrasting line and bar-chart renderings as examples.
- What you can do after
- Evaluate whether a line plot communicates an ordered relationship and simplify it for audience understanding.
Build Python Web Apps with Streamlit
A line chart is a visualization that represents ordered data points connected by line segments.
- How it is used
- Uses ordered values to reveal metric trends over time in interactive dashboards and simple simulations.
- How deep it goes
- Explains selection, filtering, aggregation, and rendering, without descending into chart-rendering internals.
- Examples
- Uses a die-roll simulator and a filtered business-metrics dashboard as concrete examples.
- What you can do after
- Build it from scratch with Streamlit, using prepared data and either its line-chart API or Plotly.
Read how Build Python Web Apps with Streamlit explains line plot →
Digital Twins in Action
A line graph is a chart that connects data values in sequence to show changes and trends, commonly over time.
- How it is used
- Reveals trends and unusual patterns in time-series sensor readings.
- How deep it goes
- Works through daily aggregation and a plotted example, but gives implementation code for sparklines rather than a full line graph.
- Examples
- Uses 6,375 temperature readings summarized across 45 days into daily lows, highs, and means.
- What you can do after
- Apply it to daily sensor summaries to identify trends and unusual readings.
Related concepts
- visualizationkind of · Visualization is the representation of data, information, or concepts in visual form to support inspection, interpretation, analysis, or communication.
- data sourceuses · A data source is an origin, system, repository, or process from which data is obtained for use or processing.
- dashboardpart of · A dashboard is a visual interface that consolidates selected data, metrics, or status information for monitoring, analysis, or decision-making.
- connectionuses · A visual grouping principle in which elements with connected forms are perceived as correlated and belonging to the same group.
- slope graphincludes · A slope graph, or slope chart, is a line-based chart that compares values at two endpoints by connecting corresponding points.
- bar chartincludes · A bar chart is a visualization that compares quantitative values for discrete categories using rectangular bars whose lengths or heights encode magnitude.
These guides are generated from the text of Manning books by Manning's knowledge graph and link to the sections they draw on. The full books are available on liveBook and at manning.com.