{"metadata":{"kernelspec":{"name":"ir","display_name":"R","language":"R"},"language_info":{"name":"R","codemirror_mode":"r","pygments_lexer":"r","mimetype":"text/x-r-source","file_extension":".r","version":"4.4.0"},"kaggle":{"accelerator":"none","dataSources":[{"sourceId":59156,"databundleVersionId":13719397,"sourceType":"competition"},{"sourceId":13108182,"sourceType":"datasetVersion","datasetId":8303395}],"dockerImageVersionId":30749,"isInternetEnabled":true,"language":"r","sourceType":"notebook","isGpuEnabled":false}},"nbformat_minor":4,"nbformat":4,"cells":[{"cell_type":"markdown","source":"# 📊 EDA 🔎 MABe Callenge 🐁🐁🐁\n\nThis notebook contains a colorfull visual 📊 Exploratory Data Analysis 🔎 using **R** and a briff explanation of how use themes for your visuals\n\nI hope 🩷 this **EDA** can be usefull, and if you have any ideas that i can include please let me know 😊","metadata":{}},{"cell_type":"markdown","source":"## **Dataset:**\n**📊 EDA 🔎 MABe Callenge 🐁🐁🐁**\n\nPreapred training data for analysis: https://www.kaggle.com/datasets/alejandravillarreal/prepared-data\n\n## **Other projects:**\n**🏥 ISIC — Skin Cancer 🔎 EDA**\n\nR: https://www.kaggle.com/code/alejandravillarreal/isic-skin-cancer-eda\n\n**🥣 Cereals - 🍎 Nutritional 🔍 EDA using R**\n\nR: https://www.kaggle.com/code/alejandravillarreal/cereals-nutritional-eda-using-r\n\n**ARC - Applying 🧮 algebra to EDA 🔎**\n\nPython: https://www.kaggle.com/code/alejandravillarreal/arc-applying-algebra-to-eda","metadata":{}},{"cell_type":"markdown","source":"# Let's See that Mice beahavior data 😸😸","metadata":{}},{"cell_type":"markdown","source":"![Let's see the Mice data](https://raw.githubusercontent.com/alejandraNvillarreal/images_notebooks/refs/heads/main/cats.jpeg)","metadata":{}},{"cell_type":"markdown","source":"## Libraries","metadata":{}},{"cell_type":"code","source":"# Visualizations\nlibrary(hrbrthemes)\nlibrary(ggthemes)\nlibrary(ggplot2)\nlibrary(gridExtra)\nlibrary(ggpubr)\nlibrary(patchwork)\n\n# Data Manipulation\nlibrary(dplyr)\n\n# Statistics\nlibrary(DescTools)","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2025-09-19T23:02:53.178277Z","iopub.execute_input":"2025-09-19T23:02:53.180499Z","iopub.status.idle":"2025-09-19T23:02:55.437885Z","shell.execute_reply":"2025-09-19T23:02:55.435979Z"},"_kg_hide-input":true,"collapsed":true,"jupyter":{"outputs_hidden":true}},"outputs":[],"execution_count":null},{"cell_type":"markdown","source":"# For new members - How to get a dataset Path\n\n![imports_datasets](https://raw.githubusercontent.com/alejandraNvillarreal/images_notebooks/refs/heads/main/download%20(3).jpeg)","metadata":{}},{"cell_type":"markdown","source":"## Just for new members - How to get a dataset Path\n\n\n**The way you can obteain link of the dataset that you want to import.**\n** * first of all you notebook need to be linket to the competition or the dataset you need**\n\n\n**How to link you notebook or import another dataset ?**\n\n![image.png](attachment:774856aa-df84-431e-8e2a-a4fc79b8516f.png)\n\n## **In case you already link your notebook**\n**serch the desire dataset (in this case is the training dataset of the competition)**\n**copy the path:**\n![image.png](attachment:afbb69b4-b4ee-40f7-9339-ab8530958d55.png)\n\n## **then you get the next path:**\n***\"/kaggle/input/MABe-mouse-behavior-detection/train.csv\"***\n\n\n## For R \n**you jsut need the part of the path after the *\"/kaggle/\"* and you need to append: *\"../\"* before the rest of the path**\n\n**examples:**\n\n**for taining dataset:**  ***\"../input/MABe-mouse-behavior-detection/train.csv\"***\n\n**for test dataset:**  ***\"../input/MABe-mouse-behavior-detection/test.csv\"***","metadata":{"_kg_hide-input":true,"_kg_hide-output":true},"attachments":{"774856aa-df84-431e-8e2a-a4fc79b8516f.png":{"image/png":"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"},"afbb69b4-b4ee-40f7-9339-ab8530958d55.png":{"image/png":"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"}}},{"cell_type":"markdown","source":"## Import 🦾 Training data\n\nIn this case i deceide to usse a prepared dataset before the visual part if you whant to review that dataset path below:\n* Preapred training data for analysis: https://www.kaggle.com/datasets/alejandravillarreal/prepared-data\n\n![rgt_cat](https://raw.githubusercontent.com/alejandraNvillarreal/images_notebooks/refs/heads/main/cat%20right.jpeg)","metadata":{}},{"cell_type":"code","source":"#importing prepared training data\ndata <- read.csv(\"../input/prepared-data/prepared_data.csv\", stringsAsFactors = FALSE)\n# Viewing the first row\nhead(data, 6)","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2025-09-19T23:04:23.107704Z","iopub.execute_input":"2025-09-19T23:04:23.109431Z","iopub.status.idle":"2025-09-19T23:04:23.162426Z","shell.execute_reply":"2025-09-19T23:04:23.160506Z"}},"outputs":[],"execution_count":null},{"cell_type":"markdown","source":"# Function of a base visualization\n\n* **Theme:** *linen*\n* **More R themes for ggplot2:** [reference/ggtheme.html](https://ggplot2.tidyverse.org/reference/ggtheme.html)\n\nThe next function help us to not need to redeclare the structuro and astetics on each visualization\n\n![lft_cat](https://raw.githubusercontent.com/alejandraNvillarreal/images_notebooks/refs/heads/main/cat%20left.jpeg)","metadata":{}},{"cell_type":"code","source":"horz_bar <- function(df, x_val, y_val, ledg, val, name){\n    ggplot(data = df, mapping = aes(x = x_val, y = reorder(y_val, val),)) +\n    geom_bar(stat = \"identity\", mapping = aes(fill = y_val, color = ledg), alpha = .7, linewidth = 1.1) +\n    labs(color = \"Behavior\") + labs(fill = \"Behavior\") +\n    geom_label(mapping = aes(label=val), fill = \"#D3D3D3\", size = 6, color = \"black\", fontface = \"bold\", hjust=.7) +\n    ggtitle(name) + xlab(\" \") + ylab(\"\") + theme_ipsum(base_family = \"sans\") +\n    theme(plot.background = element_rect(fill = \"linen\", color = \"linen\", size = 1.1),\n          plot.title = element_text(size = 20, hjust = .5, face = \"bold\"),\n          axis.title.x = element_text(size = 14, hjust = .5, face = \"italic\"),\n          axis.title.y = element_text(size = 14, hjust = .5, face = \"italic\"),\n          axis.text.x = element_text(size = 14, face = \"bold\"),\n          axis.text.y = element_text(size = 14, face = \"bold\"))\n}","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2025-09-19T23:02:55.605093Z","iopub.execute_input":"2025-09-19T23:02:55.606502Z","iopub.status.idle":"2025-09-19T23:02:55.618915Z","shell.execute_reply":"2025-09-19T23:02:55.617113Z"}},"outputs":[],"execution_count":null},{"cell_type":"markdown","source":"# 🐁 Behavior analysis by 🐁 Sex 🔎","metadata":{}},{"cell_type":"markdown","source":"So lets see the diferent behavior beetween females 🐁 and males 🐁\n\n![fight](https://raw.githubusercontent.com/alejandraNvillarreal/images_notebooks/refs/heads/main/fight.jpeg)","metadata":{}},{"cell_type":"code","source":"#splited datasets\nfemale_data <- filter(data, observed_sex == \"female\")\nmale_data <- filter(data, observed_sex == \"male\")\n\n\n#frecuency tables for dataset\nfreq_fem_act <- data.frame(cbind(Frequency = table(female_data$action), Percent = prop.table(table(female_data$action)) * 100))\nfreq_fem_act <- freq_fem_act[order(freq_fem_act$Frequency, decreasing=TRUE), ]\nfreq_fem_act\n\nfreq_male_act <- data.frame(cbind(Frequency = table(male_data$action), Percent = prop.table(table(male_data$action)) * 100))\nfreq_male_act <- freq_male_act[order(freq_male_act$Frequency, decreasing=TRUE), ]\nfreq_male_act","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2025-09-19T23:02:55.538992Z","iopub.execute_input":"2025-09-19T23:02:55.540435Z","iopub.status.idle":"2025-09-19T23:02:55.602354Z","shell.execute_reply":"2025-09-19T23:02:55.600549Z"},"collapsed":true,"jupyter":{"outputs_hidden":true}},"outputs":[],"execution_count":null},{"cell_type":"code","source":"#females graph\nfem_act <- horz_bar(\n    freq_fem_act, freq_fem_act$Frequency, row.names(freq_fem_act), row.names(freq_fem_act), freq_fem_act$Frequency, \n    \"Female Actions distribution\")\n#males full graph\nmale_act <- horz_bar(\n    freq_male_act, freq_male_act$Frequency, row.names(freq_male_act), row.names(freq_male_act), freq_male_act$Frequency, \n    \"Male Actions distribution\")\n#males top 5 graph\nmale_top <- head(freq_male_act, 5)\nmale_act_top <- horz_bar(\n    male_top, male_top$Frequency, row.names(male_top), row.names(male_top), male_top$Frequency, \n    \"TOP 5 - Male Actions distribution\")","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2025-09-19T23:02:55.621664Z","iopub.execute_input":"2025-09-19T23:02:55.623093Z","iopub.status.idle":"2025-09-19T23:02:55.862487Z","shell.execute_reply":"2025-09-19T23:02:55.860496Z"}},"outputs":[],"execution_count":null},{"cell_type":"code","source":"# grid size\noptions(repr.plot.width = 30, repr.plot.height = 15)\n\n#plot female visuals \nggarrange(\n    fem_act + theme(legend.position = \"none\"),                                 #retire the legend for the left viz\n    plot(fem_act + coord_polar() + theme(axis.text.y = element_blank())),      #retire the axis y for the right viz\n    widths = c(1.8,2.1))\n#plot male visuals\n    #In this case the male dataset was more large so for the radial visual i decide to use just the TOP 5 \nggarrange(\n    male_act + theme(legend.position = \"none\"),                                 #retire the legend for the left viz\n    plot(male_act_top + coord_polar() + theme(axis.text.y = element_blank())),  #retire the axis y for the right viz\n    widths = c(1.8,2.1))","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2025-09-19T23:06:39.597946Z","iopub.execute_input":"2025-09-19T23:06:39.599532Z","iopub.status.idle":"2025-09-19T23:06:42.331789Z","shell.execute_reply":"2025-09-19T23:06:42.328966Z"}},"outputs":[],"execution_count":null},{"cell_type":"markdown","source":"# 🐁 Behavior analysis by 🐁 Color 🔎","metadata":{}},{"cell_type":"markdown","source":"Let's analyze the diferent behavior between white 🐁, brown 🐁 and black 🐁 mouses\n\n![pwr_rngrs](https://raw.githubusercontent.com/alejandraNvillarreal/images_notebooks/refs/heads/main/Power%20Ratgers%20megafarts%F0%9F%92%99%F0%9F%92%9C%F0%9F%92%96%F0%9F%92%9A.jpeg)","metadata":{}},{"cell_type":"code","source":"#splitt data by color\nwhite <- filter(data, observed_color == \"white\")      # White mouse Datasete \nbrown <- filter(data, observed_color == \"brown\")      # Brown mouse Datasete\nblack <- filter(data, observed_color == \"black\")      # Black mouse Datasete\n\n\n#calculate frecuency tables\nfreq_white <- data.frame(cbind(Frequency = table(white$action), Percent = prop.table(table(white$action)) * 100))\nfreq_white <- freq_white[order(freq_white$Frequency, decreasing=TRUE),]\nfreq_white\n\nfreq_brown <- data.frame(cbind(Frequency = table(brown$action), Percent = prop.table(table(brown$action)) * 100))\nfreq_brown <- freq_brown[order(freq_brown$Frequency, decreasing=TRUE),]\nfreq_brown\n\nfreq_black <- data.frame(cbind(Frequency = table(black$action), Percent = prop.table(table(black$action)) * 100))\nfreq_black <- freq_black[order(freq_black$Frequency, decreasing=TRUE),]\nfreq_black","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2025-09-19T23:02:58.304864Z","iopub.execute_input":"2025-09-19T23:02:58.306633Z","iopub.status.idle":"2025-09-19T23:02:58.389359Z","shell.execute_reply":"2025-09-19T23:02:58.387598Z"},"collapsed":true,"jupyter":{"outputs_hidden":true},"_kg_hide-input":true},"outputs":[],"execution_count":null},{"cell_type":"code","source":"# White mice viz\nwhite_act <- horz_bar(\n    freq_white, freq_white$Frequency, row.names(freq_white), row.names(freq_white), freq_white$Frequency, \n    \"White Mice - Actions distribution\")\n# Brown mice viz\nbrown_act <- horz_bar(\n    freq_brown, freq_brown$Frequency, row.names(freq_brown), row.names(freq_brown), freq_brown$Frequency, \n    \"Brown Mice - Actions distribution\")\n# Black mice viz\nblack_act <- horz_bar(\n    freq_black, freq_black$Frequency, row.names(freq_black), row.names(freq_black), freq_black$Frequency, \n    \"Black Mice - Actions distribution\")\n\n#males top 6 graph\nblack_top <- head(freq_black, 6)\nblack_act_top <- horz_bar(\n    black_top, black_top$Frequency, row.names(black_top), row.names(black_top), black_top$Frequency, \n    \"TOP 6 - Black Mice - Actions distribution\")","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2025-09-19T23:02:58.392137Z","iopub.execute_input":"2025-09-19T23:02:58.393537Z","iopub.status.idle":"2025-09-19T23:02:58.522372Z","shell.execute_reply":"2025-09-19T23:02:58.520383Z"}},"outputs":[],"execution_count":null},{"cell_type":"code","source":"#plot brown mouse visuals\nggarrange(\n    brown_act + theme(legend.position = \"none\"),                                 #retire the legend for the left viz\n    plot(brown_act + coord_polar() + theme(axis.text.y = element_blank())),      #retire the axis y for the right viz\n    widths = c(1.75,2.1))\n#plot white mouse visuals \nggarrange(\n    white_act + theme(legend.position = \"none\"),                                 #retire the legend for the left viz\n    plot(white_act + coord_polar() + theme(axis.text.y = element_blank())),      #retire the axis y for the right viz\n    widths = c(1.75,2.1))\n#plot black mouse visuals\n    #In this case the dataset was more large so for the radial visual i decide to use just the TOP 6\nggarrange(\n    black_act + theme(legend.position = \"none\"),                                 #retire the legend for the left viz\n    plot(black_act_top + coord_polar() + theme(axis.text.y = element_blank())),  #retire the axis y for the right viz\n    widths = c(1.75,2.1))","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2025-09-19T23:07:49.118486Z","iopub.execute_input":"2025-09-19T23:07:49.120146Z","iopub.status.idle":"2025-09-19T23:07:53.447246Z","shell.execute_reply":"2025-09-19T23:07:53.444956Z"}},"outputs":[],"execution_count":null},{"cell_type":"markdown","source":"# 🐁 🐁 thanks for read it ☺️ 🔎","metadata":{}},{"cell_type":"markdown","source":"I'm currently working in a fully interactive dashboard.\n\nIf you have any ideas for it, or some feedback Im happy to hear it ☺️","metadata":{}},{"cell_type":"markdown","source":"![travel](https://raw.githubusercontent.com/alejandraNvillarreal/images_notebooks/refs/heads/main/on%20holiday%20hamster.jpeg)","metadata":{}}]}