LITMIR.BIZ

      1 Chapter 1Figure 1.1 The relationship between base-R and R-studio.Figure 1.2 The R-Studio IDE console.Figure 1.3 The upper left R script with basic commands and comments.Figure 1.4 Showing the code execution on line 2 of...Figure 1.5 The basic scatter plot is instantiated in the...Figure 1.6 The renewed plot with an R object in the environment.Figure 1.7 The representation of the list with varying objects.Figure 1.8 As expected the more minutes a player...Figure 1.9 The Dallas team statistics represented...

      2 Chapter 2Figure 2.1 The plots displayed with a path and...Figure 2.2 The “Nightingale Rose Diagram”...Figure 2.3 The original Nightingale Rose...Figure 2.4 The Nightingale data replotted as...Figure 2.5 The Tufte inspired...Figure 2.6 The Tufte inspired,...Figure 2.7 The basic bar chart showing the example...Figure 2.8 The side-by-side bar chart lets the use compare...Figure 2.9 The stacked bar chart demonstrating the overall difference...Figure 2.10 Since the tally of rowing...Figure 2.11 The proportional stacked bar...Figure 2.12 The swimmer data showing three dimensions of data in...Figure 2.13 An acceptable pie chart...Figure 2.14 The identical data...Figure 2.15 Even with many similar value...Figure 2.16 A complicated pie...Figure 2.17 A basic 3D bar chart example.Figure 2.18 An example ggplot baseball diamond.Figure 2.19 A basketball court with example assist data from Cleveland...Figure 2.20 A basic professional football...Figure 2.21 An example `rbokeh...Figure 2.22 The `echarts4r...

      3 Chapter 3Figure 3.1 Conceptually demonstrating...Figure 3.2 Miguel Castro’s ERA which...Figure 3.3 The PNG export of the `echarts4r` visual...Figure 3.4 Pitch type by year showing the changing...Figure 3.5 The JavaScript...Figure 3.6 A basic explanation...Figure 3.7 The box plots demonstrate an increasing velocity for “CH...Figure 3.8 A screenshot of the JavaScript box plots for...Figure 3.9 The pitch location heatmaps demonstrate...Figure 3.10 Miguel Castro’s...Figure 3.11 The faceted hexbin with JavaScript user tooltips.Figure 3.12 The year-over-year change in swing probability for the batter.Figure 3.13 The different hit locations by season.Figure 3.14 The proportion of hits by predefined zone...Figure 3.15 The comparison between...

      4 Chapter 4Figure 4.1 Demonstrating KNN with...Figure 4.2 Adjusted for multi-class outcomes, player...Figure 4.3 Player data with...Figure 4.4 The assigned points for each cluster.Figure 4.5 The centroids move to minimize either the mean or...Figure 4.6 The centroids placed where no more points are reassigned...Figure 4.7 The difference between distances measures.Figure 4.8 A visual comparison of draft to non-draft by position.Figure 4.9 This visual compares 40yrd times...Figure 4.10 A barbell Dot Plot demonstrating the 40-yard sprint...Figure 4.11 The neighbor to accuracy relationship demonstrating...Figure 4.12 The training set ROC curve showing a...Figure 4.13 The error curve demonstrating that the RMSE error metric...

      5 Chapter 5Figure 5.1 The PPG kernel density plot showing the most...Figure 5.2 Kernel density plots for each actual...Figure 5.3 The proportional coefficient...Figure 5.4 The winning team frequency by...Figure 5.5 The field goal percentage distribution...

      6 Chapter 6Figure 6.1 A full join where all data in table A is appended to...Figure 6.2 The area chart with...Figure 6.3 The star-shaped word cloud showing “middle...Figure 6.4 An inner join between two tables.Figure 6.5 The ggplot style radar chart, showing more love...Figure 6.6 The cumulative sum polarity area chart.Figure 6.7 An example network graph of user nodes and edge connections.Figure 6.8 The default network plot for...Figure 6.9 The simplified network...Figure 6.10 The top and bottom decile polarity forum commentors.Figure 6.11 The polarity bars with all users. As a user’s mouse rolls

      7 Chapter 7Figure 7.1 The “Baker Mayfield...Figure 7.2 The QB selection frequency chart.Figure 7.3 The DST bar chart from 'echarts4r'.Figure 7.4 The facets bar charts by position.Figure 7.5 The relationship of uncertainty and...Figure 7.6 The HTML-based scatter...

      8 Chapter 8Figure 8.1 Akron’s players by shots demonstrate a power...Figure 8.2 The team...Figure 8.3 The Cleveland dot plot showing Akron’s dispersal...Figure 8.4 The Cleveland dot plot demonstrating opposing team Goal...Figure 8.5 The cumulative shots over the season where the slope...Figure 8.6 The adjusted smoothed line...

      1 Chapter 1Table 1.1 Three simple control flows in R including...Table 1.2 Common R data types...Table 1.3 The...

      2 Chapter 2Table 2.1 Sixty seemingly unrelated data points.Table 2.2 A summary of the types of bar charts and when to use them.Table 2.3 The robust sportyR...

      3 Chapter 3Table 3.1 An abridged `People` data frame...Table 3.2 The single row for Miguel Castro player information.Table 3.3 Miguel Castro’s year-over-year pitch type tally by year.Table 3.4 Miguel Castros’ pitch type by year as...Table 3.5 The reorientation of the pitch data to the long format.Table 3.6 Showing the maximum value in 2017 being...Table 3.7 The x–y coordinates for two strike subzones.Table 3.8 The player’s proportion of hits for both seasons.

      4 Chapter 4Table 4.1 The primary football positions...Table 4.2 The...Table 4.3 Illustrative...Table 4.4 The result of applying...Table 4.5 The summary statistics including average, minimum,...Table 4.6 The training set confusion matrix results.Table 4.7 Showing individual class probabilities which...Table 4.8 The training set confusion matrix...Table 4.9 The median cluster summary statistics.Table 4.10 The Mediod cluster assignments as...

      5 Chapter 5Table 5.1 A portion of the women’s basketball data.Table 5.2 The approximate three...Table 5.3 The model’s in-sample confusion matrix, where...Table 5.4 External Kappa context from a Biochemia Medica article.Table 5.5 A comparison of model metrics...Table 5.6 The first six records of the winning season teams’ data.Table 5.7 The summary winning team statistic and model data.Table 5.8 The inclusion of Green Bay among these...

      6 Chapter 6Table 6.1 A portion of the 1641 wordnet_affect lexicon.Table 6.2 The small, customized...Table 6.3 A portion of the comments and posts by day.Table 6.4 A portion of the bigram frequency data frame.Table 6.5 A portion of the tidy unigram data from cricket forum postsTable 6.6 The count and grouping of...Table 6.7 A selection of the left join table...Table 6.8 A selection of comment identifiers...Table 6.9 A portion of the incident matrix where user “0”...

      7 Chapter 7Table 7.1 A portion of the player...Table 7.2 A single player’...Table 7.3 A portion of the cleaned up...Table 7.4 The smaller player data set with...Table 7.5 A portion of the...Table 7.6 The one hot encoding for...Table 7.7 The transposed dummy variable matrix for a small...Table 7.8 The encoded data, showing a player...Table 7.9 Where Baker Mayfield’s game points were simulated...Table 7.10 The lineup attributes...Table 7.11 The optimal lineup given the point totals for the...Table 7.12 The most selected...Table 7.13 The joined optimal lineup tally and point information.Table 7.14 The preference...Table 7.15 The optimal lineup according to the optimization analysis...

      8 Chapter 8Table 8.1 The MAC teams within this chapte’s data.Table 8.2 The sequence matrix demonstrating sequence action tallies.Table 8.3 The outlier on goal rate...Table 8.4 The cumulative results within a...Table 8.5 The tabulation and proportion of Akron’s play type.Table 8.6 Akron’s play transition state for the 2019 season.

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