Summary
The issue of gaps between tiles when using variable width with geom_tile() in ggplot2 can be confusing, especially when compared to the seamless output of geom_rect(). This article aims to explore the root cause of this issue, its real-world impact, and provide a solution to achieve seamless tiles.
Root Cause
The gaps between tiles are due to the way geom_tile() handles variable widths. The alignment of tiles is not adjusted according to the width, resulting in gaps. Key factors contributing to this issue include:
- Tile width calculation: The width of each tile is calculated separately, leading to slight discrepancies in the overall alignment.
- Rounding errors: Rounding errors can occur when calculating the positions of the tiles, further contributing to the gaps.
Why This Happens in Real Systems
In real-world systems, this issue can arise when dealing with variable-sized data points, such as time series data with varying intervals or spatial data with different densities. The gaps between tiles can lead to:
- Misinterpretation of data: Gaps can give a false impression of missing data or incorrect trends.
- Aesthetically unpleasing visuals: The gaps can make the visualization look incomplete or poorly designed.
Real-World Impact
The impact of this issue can be significant, especially in data-intensive applications where accurate representation of data is crucial. Some examples of real-world impact include:
- Financial analysis: Inaccurate representation of financial data can lead to incorrect conclusions and decisions.
- Scientific research: Gaps in data visualization can obscure important trends and patterns, leading to incorrect interpretations.
Example or Code
library(ggplot2)
df <- structure(list(x = c(0, 21.026200056076, 35.0927000045776, 62.523099899292, 89.1552000045776, 119.409399986267, 150.959199905396, 182.923199892044, 216.236999988556, 246.544800043106, 275.653599977493, 305.506399869919, 334.649699926376, 354.44019985199, 374.723899841309, 394.026599884033, 414.470799922943, 434.197499990463, 454.703999996185, 474.275099992752, 497.525599956512, 522.205100059509, 542.863199949265, 563.00469994545, 590.873600006104, 621.759700059891, 647.591799974442, 678.530400037766, 695.489300012589, 717.778300046921, 742.79439997673, 767.416599988937, 791.24549984932), width = c(21.026200056076, 14.0664999485016, 27.4303998947144, 26.6321001052856, 30.2541999816895, 31.5497999191284, 31.9639999866486, 33.3138000965118, 30.3078000545502, 29.1087999343872, 29.8527998924255, 29.1433000564575, 19.7904999256134, 20.2836999893188, 19.3027000427246, 20.4442000389099, 19.7267000675201, 20.506500005722, 19.5710999965668, 23.2504999637604, 24.6795001029968, 20.6580998897552, 20.1414999961853, 27.8689000606537, 30.8861000537872, 25.8320999145508, 30.938600063324, 16.958899974823, 22.2890000343323, 25.0160999298096, 24.622200012207, 23.8288998603821, 26.350800037384)), class = "data.frame", row.names = c(NA, -33L))
ggplot(df) +
geom_tile(aes(x = x, y = '1', width = width, height = 0.5), fill = 'grey75', color = 'black')How Senior Engineers Fix It
To fix the issue, senior engineers can use the following approaches:
- Adjust the alignment: Adjust the alignment of the tiles to match the variable widths.
- Use geom_rect(): Use
geom_rect()instead ofgeom_tile()to avoid the alignment issue. - Customize the visualization: Customize the visualization to accommodate the variable widths, such as using a different type of geom or adjusting the scales.
Why Juniors Miss It
Junior engineers may miss this issue due to:
- Lack of experience: Limited experience with ggplot2 and data visualization can lead to overlooking the alignment issue.
- Insufficient testing: Inadequate testing of the visualization with different datasets and scenarios can fail to reveal the problem.
- Unfamiliarity with geom_tile(): Lack of understanding of how
geom_tile()handles variable widths can lead to unexpected gaps in the visualization.