Added interactive dashboard built with Preswald

data/sample.csv

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+decimalLatitude,decimalLongitude,speciesQueried,country,year,lifeStage
+-3.4653,-62.2159,Callithrix jacchus,Brazil,2018,Adult
+-4.2121,-63.0012,Callithrix penicillata,Brazil,2019,Juvenile
+5.0000,-74.0000,Cebuella pygmaea,Colombia,2017,Adult
+-1.4563,-78.9874,Leontopithecus rosalia,Ecuador,2020,Subadult
+-12.4634,-55.6658,Saguinus oedipus,Brazil,2016,Adult
+2.0500,-75.2500,Saguinus mystax,Colombia,2021,Juvenile
+-9.1900,-67.8280,Leontopithecus chrysomelas,Brazil,2015,Adult
+0.0000,-60.0000,Callithrix geoffroyi,Venezuela,2019,Subadult
+4.5709,-74.2973,Cebuella pygmaea,Colombia,2022,Adult
+-15.7797,-47.9297,Callithrix jacchus,Brazil,2023,Juvenile

hello.py

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+import pandas as pd
+import plotly.express as px
+import preswald
+
+# Load dataset
+df = pd.read_csv('data/sample.csv')
+
+# Geographic Scatter Plot
+fig = px.scatter_geo(
+    df,
+    lat="decimalLatitude",
+    lon="decimalLongitude",
+    hover_name="speciesQueried",
+    color="country",
+    title="Geographical Distribution of Callitrichidae Specimens",
+    projection="natural earth"
+)
+
+# Density Heatmap
+hotspot_map = px.density_mapbox(
+    df,
+    lat="decimalLatitude",
+    lon="decimalLongitude",
+    radius=8,
+    zoom=3,
+    color_continuous_scale="Viridis",
+    mapbox_style="carto-positron",
+    title="Spatial Density Analysis of Callitrichidae Populations"
+)
+
+# Species Richness Bar Chart
+richness = df.groupby("country")["speciesQueried"].nunique().reset_index(name="richness")
+richness_plot = px.bar(
+    richness.sort_values("richness", ascending=False),
+    x="country",
+    y="richness",
+    title="Callitrichidae Species Richness by Geographic Region"
+)
+
+# Hierarchical Distribution TreeMap
+df_treemap = df.groupby(["country", "speciesQueried"]).size().reset_index(name="count")
+treemap_plot = px.treemap(
+    df_treemap,
+    path=["country", "speciesQueried"],
+    values="count",
+    color="count",
+    title="Taxonomic and Geographic Distribution of Callitrichidae Specimens"
+)
+
+# Life Stage Trend Line Plot
+life_stage_trend = df[df["lifeStage"].notna() & (df["lifeStage"].str.lower() != "unknown")]
+life_stage_plot_data = life_stage_trend.groupby(["year", "lifeStage"]).size().reset_index(name="count")
+life_stage_plot = px.line(
+    life_stage_plot_data,
+    x="year",
+    y="count",
+    color="lifeStage",
+    title="Ontogenetic Distribution of Callitrichidae Observations: Temporal Analysis"
+)
+
+# ───────────────────── Display on Preswald UI ─────────────────────
+
+preswald.text("# 🐒 Biogeographical Analysis of Callitrichidae Distribution Patterns")
+
+preswald.text("## 📍 Spatial Distribution Analysis")
+preswald.text("Figure 1 shows the global locations of documented Callitrichidae specimens by country.")
+preswald.plotly(fig)
+
+preswald.text("## 🌐 Population Density Assessment")
+preswald.text("Figure 2 estimates specimen density and helps identify biodiversity hotspots.")
+preswald.plotly(hotspot_map)
+
+preswald.text("## 🌱 Species Richness Evaluation")
+preswald.text("Figure 3 shows how many unique species were observed per country.")
+preswald.plotly(richness_plot)
+
+preswald.text("## 🧬 Taxonomic Distribution by Region")
+preswald.text("Figure 4 illustrates taxonomic and geographic spread using a hierarchical treemap.")
+preswald.plotly(treemap_plot)
+
+preswald.text("## 📈 Ontogenetic Temporal Distribution")
+preswald.text("Figure 5 tracks specimen counts by life stage over time.")
+preswald.plotly(life_stage_plot)

preswald.toml

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+[project]
+title = "Preswald Project"
+version = "0.1.0"
+port = 8501
+slug = "my-app-839952"
+entrypoint = "hello.py"
+
+[branding]
+name = "Preswald Project"
+logo = "images/logo.png"
+favicon = "images/favicon.ico"
+primaryColor = "#F89613"
+
+[data.sample_csv]
+type = "csv"
+path = "data/sample.csv"
+
+[logging]
+level = "INFO"
+format = "%(asctime)s - %(name)s - %(levelname)s - %(message)s"

secrets.toml

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+# Store your sensitive configuration here
+# This file is gitignored by default