"
]
},
{
"cell_type": "markdown",
"id": "ce2def38",
"metadata": {
"slideshow": {
"slide_type": "slide"
}
},
"source": [
"# Plan for Lecture \n",
"\n",
"1. Announcements \n",
"2. Geovisulization \n",
"3. Geographical Analysis Workflow\n",
"4. Choropleth mapping \n",
"5. Classification Types"
]
},
{
"cell_type": "markdown",
"id": "fcfffe7e",
"metadata": {
"slideshow": {
"slide_type": "slide"
}
},
"source": [
"# GeoVisualization \n",
"\n",
"* Process of interactively visualizing geographic information in any of the steps in spatial analyses, \n",
"* Originated in cartography, geovis was pioneered under the ledership of Alan MacEachren (Penn State), who developed tools and methods for interactive exploratory data analysis. \n",
"* A core argument for geovisualization is that visual thinking using maps is integral to the scientific process and hypothesis generation, and the role of maps grew beyond communicating the end results of an analysis or documentation process. \n",
"* Geovis interacts with cartography, visual analytics, information visualization, scientific visualization, statistics, computer science, art-and-design, and cognitive science. \n",
"\n",
"*Source: https://gistbok.ucgis.org/bok-topics/geovisualization* "
]
},
{
"cell_type": "markdown",
"id": "8cdf435b",
"metadata": {
"slideshow": {
"slide_type": "subslide"
}
},
"source": [
"|||\n",
"|---|---|\n",
"|||\n",
"|Cartography Cube|Swoopy Framework|"
]
},
{
"cell_type": "markdown",
"id": "284db83c",
"metadata": {
"slideshow": {
"slide_type": "subslide"
}
},
"source": [
"# What does geoviz look like in practice? \n",
"\n",
""
]
},
{
"cell_type": "markdown",
"id": "9c7b9644",
"metadata": {
"slideshow": {
"slide_type": "slide"
}
},
"source": [
"# Skills for GeoVisualization \n",
"\n",
"* GUI-based tools and scripting languages (Processing, Python, D3JS)\n",
"* Data processing skills\n",
"* Analytical skills (statistics)\n",
"* Visualization skills"
]
},
{
"cell_type": "markdown",
"id": "69f50b87",
"metadata": {
"slideshow": {
"slide_type": "subslide"
}
},
"source": [
"# Typical Geovisualization Workflow \n",
"\n",
"* Raw data contains more information than we can visualize effectively \n",
"* Thus, good understanding of visulization techniques is required \n",
" * cluttered displays, overplotting\n",
" * --> aggregate data, highlighting interesting aspects of data\n",
" * if visualization is interative a **user** can explore the data and find **interesting** \n",
"* visual displays \n",
"* visual variables (Bertin) \n",
"* UI and UX design "
]
},
{
"cell_type": "markdown",
"id": "28dfa6ab",
"metadata": {
"slideshow": {
"slide_type": "subslide"
}
},
"source": [
"# Typical Data Analysis (Lab) Workflow \n",
"\n",
"* **Find the data (Cal Fire)**\n",
"* **Pre-process the data: import, inspect visually, look at missing values, filter, drop.**\n",
"* **Exploratory Data Analysis (GEOVIZ). Generate visual and pose interesting questions about data (descriptive statistics)**\n",
"* Data Analysis (inferential statistics) \n",
"* Present Findings"
]
},
{
"cell_type": "markdown",
"id": "ce345f23",
"metadata": {
"slideshow": {
"slide_type": "subslide"
}
},
"source": [
"# Data Analysis Example - California Wildfires \n",
"\n",
"1. Finding data \n",
" 1. Calfire publishes data in .gdb format, which is not straight-forward to analyze in Python (What software can we use to analyze it?) \n",
" 2. Use terminal command 'wget' to download the data via URL from the internet \n",
" 3. Find and download mannually ([try it now](https://gis.data.ca.gov/maps/CALFIRE-Forestry::california-fire-perimeters-all-1))\n",
" 4. Host on web services that provide readable url links and read via Pandas 'read_csv' function"
]
},
{
"cell_type": "markdown",
"id": "aaef4ab6",
"metadata": {
"slideshow": {
"slide_type": "subslide"
}
},
"source": [
"# Brainstorm Exercise\n",
"\n",
"> Working with your table, illicit interesting questions about wildfires in CA\n",
"\n",
"> Think about variables that are already in the data set \n",
" \n",
"> What new variables can we generate that will help us answer the questions "
]
},
{
"cell_type": "code",
"execution_count": 1,
"id": "69421369",
"metadata": {
"slideshow": {
"slide_type": "subslide"
}
},
"outputs": [],
"source": [
"# copied form the lab "
]
},
{
"cell_type": "markdown",
"id": "e4b3bd55",
"metadata": {
"slideshow": {
"slide_type": "slide"
}
},
"source": [
"# Data Analysis Example - California Wildfires \n",
"\n",
"2. Pre-process the data \n",
" 1. remove variables that you will not be using (if necessary) \n",
" 2. subset the data to your study area \n",
" 3. convert variables for calculation (float --> int; string --> datetime; etc.) "
]
},
{
"cell_type": "markdown",
"id": "c34757e0",
"metadata": {
"slideshow": {
"slide_type": "subslide"
}
},
"source": [
"# Note on naming conventions in Python\n",
"\n",
"* Never use the characters ‘l’ (lowercase letter el), ‘O’ (uppercase letter oh), or ‘I’ (uppercase letter eye) as single character variable names. In some fonts, these characters are indistinguishable from the numerals one and zero. When tempted to use ‘l’, use ‘L’ instead.\n",
"* Class names should normally use the CapWords convention. But we do not use classes in this class! \n",
"* Function names should be lowercase, with words separated by underscores as necessary to improve readability. Variable names follow the same convention as function names.\n",
"\n",
"More info in official [Python docs](https://peps.python.org/pep-0008/#prescriptive-naming-conventions) "
]
},
{
"cell_type": "code",
"execution_count": 2,
"id": "16a68765",
"metadata": {
"slideshow": {
"slide_type": "subslide"
}
},
"outputs": [],
"source": [
"import pandas as pd\n",
"import geopandas as gpd\n",
"import numpy as np\n",
"import matplotlib.pyplot as plt"
]
},
{
"cell_type": "code",
"execution_count": 3,
"id": "c3b79eac",
"metadata": {
"slideshow": {
"slide_type": "subslide"
}
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"(5250, 8)\n",
"\n"
]
}
],
"source": [
"fires = gpd.read_file('https://github.com/barguzin/geo_data/raw/main/fires.zip')\n",
"print(fires.shape) \n",
"print(type(fires))"
]
},
{
"cell_type": "code",
"execution_count": 4,
"id": "62ec9459",
"metadata": {
"slideshow": {
"slide_type": "subslide"
}
},
"outputs": [
{
"data": {
"text/html": [
"
"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"fires_per_year = fires.groupby(\"YEAR_\")[\"INC_NUM\"].count().reset_index()\n",
"fires_per_year.set_index('YEAR_', inplace=True)\n",
"fires_per_year.plot(figsize=(16,4))"
]
},
{
"cell_type": "code",
"execution_count": 8,
"id": "9b8d2e8c",
"metadata": {
"slideshow": {
"slide_type": "subslide"
}
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"(205, 9)\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"C:\\Users\\noibar\\AppData\\Local\\Temp\\ipykernel_22136\\270685699.py:6: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" fires2021.drop('UNIT_ID', inplace=True, axis=1)\n",
"C:\\Users\\noibar\\anaconda3\\envs\\geo_env\\lib\\site-packages\\geopandas\\geodataframe.py:1456: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" super().__setitem__(key, value)\n",
"C:\\Users\\noibar\\anaconda3\\envs\\geo_env\\lib\\site-packages\\geopandas\\geodataframe.py:1456: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" super().__setitem__(key, value)\n",
"C:\\Users\\noibar\\anaconda3\\envs\\geo_env\\lib\\site-packages\\geopandas\\geodataframe.py:1456: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" super().__setitem__(key, value)\n"
]
}
],
"source": [
"# subset the data to only include one year \n",
"fires2021 = fires.loc[fires['YEAR_']=='2021']\n",
"print(fires2021.shape) \n",
"\n",
"# drop a variable \n",
"fires2021.drop('UNIT_ID', inplace=True, axis=1) \n",
"\n",
"# convert data types \n",
"fires2021['ALARM_DATE'] = pd.to_datetime(fires2021.ALARM_DATE)\n",
"fires2021['CONT_DATE'] = pd.to_datetime(fires2021.CONT_DATE)\n",
"\n",
"# calculate duration\n",
"fires2021['dur_days'] = (fires2021.CONT_DATE - fires2021.ALARM_DATE).dt.days\n",
"\n",
"# get the month start of fires \n",
"fires2021['month_started'] = fires2021.ALARM_DATE.dt.month"
]
},
{
"cell_type": "code",
"execution_count": 9,
"id": "19debace",
"metadata": {
"slideshow": {
"slide_type": "subslide"
}
},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"C:\\Users\\noibar\\anaconda3\\envs\\geo_env\\lib\\site-packages\\geopandas\\geodataframe.py:1456: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" super().__setitem__(key, value)\n"
]
},
{
"data": {
"text/html": [
"
"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"# find average dur of fires \n",
"print('average duration of fires in 2021:', fires2021.dur_days.mean())\n",
"\n",
"# add labels \n",
"labs = ['Jan', 'Feb', 'Mar', 'Apr', 'May', 'Jun', 'Jul', 'Aug', 'Sep', 'Oct', 'Nov', 'Dec']\n",
"\n",
"# get unique values and tally them \n",
"# this works well for count() function \n",
"# when you need to calculate total number of something\n",
"ax = fires2021.month_started.value_counts().sort_index().plot(kind='bar')\n",
"ax.set_xticklabels(labs, rotation=45, fontsize=14);"
]
},
{
"cell_type": "code",
"execution_count": 12,
"id": "9bcd0e9f",
"metadata": {
"slideshow": {
"slide_type": "subslide"
}
},
"outputs": [
{
"data": {
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\n",
"text/plain": [
"
"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"from matplotlib.ticker import FormatStrFormatter\n",
"# another way to aggregate data \n",
"# when you need mean() or sum()\n",
"# total acreage by day of week for start of the fire \n",
"fires_per_dow = fires2021.groupby('dow')['GIS_ACRES'].sum().reset_index()\n",
"fires_per_dow.set_index(\"dow\", inplace=True)\n",
"\n",
"# add labels \n",
"labs = ['Mon', 'Tue', 'Wed', 'Thu', 'Fri', 'Sat', 'Sun']\n",
"\n",
"ax = fires_per_dow.plot(kind='bar')\n",
"ax.set_xticklabels(labs, rotation=45, fontsize=14);\n",
"ax.set_xlabel(''); # remove 'dow' label \n",
"\n",
"ax.yaxis.set_major_formatter(FormatStrFormatter('%.0f'))"
]
},
{
"cell_type": "markdown",
"id": "bbd512f8",
"metadata": {
"slideshow": {
"slide_type": "slide"
}
},
"source": [
"# Add a spatial component to our analysis \n",
"\n",
"### Because this is an Intermediate Geographic Analysis Course \n",
"\n",
"#### 🙃"
]
},
{
"cell_type": "code",
"execution_count": 13,
"id": "0fbc5af8",
"metadata": {
"slideshow": {
"slide_type": "subslide"
}
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"(58, 2)\n",
"epsg:3310 epsg:3310\n"
]
},
{
"data": {
"text/html": [
"
\n",
"\n",
"
\n",
" \n",
"
\n",
"
\n",
"
county_name
\n",
"
geometry
\n",
"
\n",
" \n",
" \n",
"
\n",
"
0
\n",
"
Alameda
\n",
"
MULTIPOLYGON (((-203097.930 -10755.124, -20094...
\n",
"
\n",
"
\n",
"
1
\n",
"
Alpine
\n",
"
POLYGON ((-6288.628 76303.334, 3042.528 84440....
\n",
"
\n",
"
\n",
"
2
\n",
"
Amador
\n",
"
POLYGON ((-89497.637 53052.537, -89492.962 546...
\n",
"
\n",
"
\n",
"
3
\n",
"
Butte
\n",
"
POLYGON ((-161923.480 144686.420, -164426.638 ...
\n",
"
\n",
"
\n",
"
4
\n",
"
Calaveras
\n",
"
POLYGON ((-76796.914 1747.218, -80494.997 6443...
\n",
"
\n",
" \n",
"
\n",
"
"
],
"text/plain": [
" county_name geometry\n",
"0 Alameda MULTIPOLYGON (((-203097.930 -10755.124, -20094...\n",
"1 Alpine POLYGON ((-6288.628 76303.334, 3042.528 84440....\n",
"2 Amador POLYGON ((-89497.637 53052.537, -89492.962 546...\n",
"3 Butte POLYGON ((-161923.480 144686.420, -164426.638 ...\n",
"4 Calaveras POLYGON ((-76796.914 1747.218, -80494.997 6443..."
]
},
"execution_count": 13,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# read CA counties \n",
"ca_counties = gpd.read_file('https://raw.githubusercontent.com/codeforgermany/click_that_hood/main/public/data/california-counties.geojson')\n",
"ca_counties = ca_counties[['name', 'geometry']]\n",
"ca_counties.columns=['county_name', 'geometry']\n",
"\n",
"# reproject \n",
"ca_counties = ca_counties.to_crs(fires2021.crs)\n",
"\n",
"print(ca_counties.shape)\n",
"print(ca_counties.crs, fires2021.crs)\n",
"\n",
"ca_counties.head()"
]
},
{
"cell_type": "markdown",
"id": "1b35307a",
"metadata": {
"slideshow": {
"slide_type": "subslide"
}
},
"source": [
"# Spatial Join 101 \n",
"\n",
"* A spatial join uses binary predicates (basic geometric operations) such as intersects and crosses to combine two GeoDataFrames based on the spatial relationship between their geometries. \n",
"* A common use case might be a spatial join between a point layer and a polygon layer where you want to retain the point geometries (**target features**) and grab the attributes of the intersecting polygons (**join features**). \n",
"\n",
""
]
},
{
"cell_type": "markdown",
"id": "2989f613",
"metadata": {
"slideshow": {
"slide_type": "subslide"
}
},
"source": [
"* A one-to-one operation will join a single feature from the join features into the target features. \n",
"\n",
"\n",
"* One-to-many operation will join all the features by creating multiple overlapping records. Each duplicate record contains the records from the joining features.\n",
""
]
},
{
"cell_type": "code",
"execution_count": 14,
"id": "5e5e77d0",
"metadata": {
"slideshow": {
"slide_type": "subslide"
}
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"(205, 10)\n",
"(226, 12)\n"
]
}
],
"source": [
"print(fires2021.shape) \n",
"fires2021_with_counties = gpd.sjoin(fires2021, ca_counties)\n",
"print(fires2021_with_counties.shape) "
]
},
{
"cell_type": "markdown",
"id": "ea9372e3",
"metadata": {},
"source": [
"# Disclaimer \n",
"\n",
"### When we do spatial join on the data with two polygon layers that are not aligned (i.e. we have fires geometries that are not contained within just one county), we will end up with duplicated records! \n",
"\n",
"### Thus, we will be overestimating totals and calculations will be imprecise! "
]
},
{
"cell_type": "code",
"execution_count": 15,
"id": "7b7fbb8d",
"metadata": {
"slideshow": {
"slide_type": "subslide"
}
},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"
"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"# calc total area of fires in CA counties in 2021 \n",
"# use 'dropna=False' to keep all counties (even those that had zero fires)\n",
"tot_by_county21 = fires2021_with_counties.groupby('county_name', dropna=False)['INC_NUM'].count().reset_index()\n",
"\n",
"# use non-spatial join to add geometries to the calculated dataframe \n",
"# please note that we join to the left dataframe by default \n",
"# thus if our left dataframe is geopandas the resulting dataframe \n",
"# will also be geopandas\n",
"tot_by_county_geom21 = pd.merge(ca_counties, tot_by_county21, on='county_name', how='outer') \n",
"\n",
"# fill in missing with zeroes \n",
"tot_by_county_geom21.fillna(0, inplace=True)\n",
"\n",
"# count of fires is stored in column 'INC_NUM'\n",
"tot_by_county_geom21.plot(column='INC_NUM', legend=True, cmap='Reds');"
]
},
{
"cell_type": "code",
"execution_count": 17,
"id": "ac1ea4ad",
"metadata": {
"slideshow": {
"slide_type": "subslide"
}
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"(5243, 9)\n",
"(5598, 11)\n"
]
}
],
"source": [
"# do the same for entire California \n",
"print(fires.shape) \n",
"fires_with_counties = gpd.sjoin(fires, ca_counties)\n",
"print(fires_with_counties.shape) "
]
},
{
"cell_type": "code",
"execution_count": 18,
"id": "3605134b",
"metadata": {
"slideshow": {
"slide_type": "subslide"
}
},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"
"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"# calc total area of fires in CA counties in 2021 \n",
"# use 'dropna=False' to keep all counties (even those that had zero fires)\n",
"tot_by_county = fires_with_counties.groupby('county_name', dropna=False)['INC_NUM'].count().reset_index()\n",
"\n",
"# use non-spatial join to add geometries to the calculated dataframe \n",
"# please note that we join to the left dataframe by default \n",
"# thus if our left dataframe is geopandas the resulting dataframe \n",
"# will also be geopandas\n",
"tot_by_county_geom = pd.merge(ca_counties, tot_by_county, on='county_name', how='outer') \n",
"\n",
"# fill in missing with zeroes \n",
"tot_by_county_geom.fillna(0, inplace=True)\n",
"\n",
"# count of fires is stored in column 'INC_NUM'\n",
"tot_by_county_geom.plot(column='INC_NUM', legend=True, cmap='Blues');"
]
},
{
"cell_type": "code",
"execution_count": 19,
"id": "6892933f",
"metadata": {
"slideshow": {
"slide_type": "subslide"
}
},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"
"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"fig, ax = plt.subplots(1,2, figsize=(12,6))\n",
"\n",
"tot_by_county_geom21.plot(column='INC_NUM', legend=True, cmap='Reds', ax=ax[0]);\n",
"ax[0].set_title('Total Number of Fires in CA\\n in 2021');\n",
"tot_by_county_geom.plot(column='INC_NUM', legend=True, cmap='Blues', ax=ax[1]);\n",
"ax[1].set_title('Total Number of Fires in CA\\n in 1910-2021');"
]
},
{
"cell_type": "markdown",
"id": "b50a2144",
"metadata": {
"slideshow": {
"slide_type": "slide"
}
},
"source": [
"# Choropleth Maps \n",
"\n",
"* Geographic maps that display statistical information encoded in a color palette. \n",
"* Display non-geographic attributes or variables on a geographic map. \n",
"* The word choropleth stems from the root “choro”, meaning “region”. As such choropleth maps represent data at the regional level, and are appropriate for areal unit data where each observation combines a value of an attribute and a geometric figure, usually a polygon. "
]
},
{
"cell_type": "markdown",
"id": "dec5cfb4",
"metadata": {
"slideshow": {
"slide_type": "subslide"
}
},
"source": [
"# Drawing Choropleth Maps\n",
"\n",
"1. Select a number of groups smaller than into which all values in our dataset will be mapped to; \n",
"2. Identify a classification algorithm that executes mapping; \n",
"3. Reduce all values in our data into corresponding number of groups, \n",
"4. Assign color to each group. \n",
"\n",
"> In broad terms, the classification scheme defines the number of classes as well as the rules for assignment; while a good symbolization conveys information about the value differentiation across classes. Source: Geographic Data Science"
]
},
{
"cell_type": "markdown",
"id": "009e2020",
"metadata": {
"slideshow": {
"slide_type": "subslide"
}
},
"source": [
"# Quantitative Data Classification\n",
"\n",
"> Partition the attribute values into mutually exclusive and exhaustive groups\n",
"\n",
"$$\n",
"c_j < y_i \\le c_{j+1} \\ \\forall y_i \\in C_{j}\n",
"$$\n",
"\n",
"where $c_j$ and $c_{j+1}$ are lower and upper boundaryfor each of the $C_j$ groups and $y_i$ are observations."
]
},
{
"cell_type": "markdown",
"id": "c40d8b0c",
"metadata": {
"slideshow": {
"slide_type": "subslide"
}
},
"source": [
"# Quantitative Data Classifications\n",
"\n",
""
]
},
{
"cell_type": "code",
"execution_count": 20,
"id": "852f5046",
"metadata": {
"slideshow": {
"slide_type": "subslide"
}
},
"outputs": [
{
"data": {
"image/png": "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\n",
"text/plain": [
"
"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"import seaborn as sns \n",
"\n",
"# Plot histogram\n",
"ax = sns.histplot(fires[\"dur_days\"], bins=5)\n",
"# Add rug on horizontal axis\n",
"sns.rugplot(fires[\"dur_days\"], height=0.02, color=\"red\", ax=ax);"
]
},
{
"cell_type": "code",
"execution_count": 21,
"id": "76083b30",
"metadata": {
"slideshow": {
"slide_type": "subslide"
}
},
"outputs": [
{
"data": {
"text/plain": [
"count 5243.00000\n",
"mean 15.27427\n",
"std 29.13632\n",
"min 1.00000\n",
"25% 1.00000\n",
"50% 4.00000\n",
"75% 11.00000\n",
"max 222.00000\n",
"Name: dur_days, dtype: float64"
]
},
"execution_count": 21,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"fires.dur_days.describe()"
]
},
{
"cell_type": "code",
"execution_count": 22,
"id": "1bc1e6e4",
"metadata": {
"slideshow": {
"slide_type": "subslide"
}
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"counts: [4698. 293. 182. 60. 10.]\n",
"bins: [ 1. 45.2 89.4 133.6 177.8 222. ]\n"
]
}
],
"source": [
"counts, bins, patches = ax.hist(fires[\"dur_days\"], bins=5)\n",
"\n",
"# The counts object captures how many observations each category in the classification has\n",
"print('counts:', counts)\n",
"\n",
"# The bin object stores these break points we are interested in when considering classification schemes \n",
"# (the patches object can be ignored in this context, as it stores the geometries of the histogram plot)\n",
"print('bins:', bins)"
]
},
{
"cell_type": "markdown",
"id": "83740578",
"metadata": {
"slideshow": {
"slide_type": "slide"
}
},
"source": [
"# Equal Intervals\n",
"\n",
"* For a given value of $k$, *equal intervals classification* splits the range of the attribute space into equal length intervals, with each interval having a width $w-\\frac{x_0 - x_{n-1}}{k}$. \n",
"* Equal intervals have the dual advantages of simplicity and ease of interpretation. \n",
"* Because this rule only considers the extreme values of the distribution this can result in one or more classes being sparse. "
]
},
{
"cell_type": "code",
"execution_count": 23,
"id": "6ffec535",
"metadata": {
"slideshow": {
"slide_type": "subslide"
}
},
"outputs": [
{
"data": {
"text/plain": [
"EqualInterval \n",
"\n",
" Interval Count\n",
"------------------------\n",
"[ 1.00, 45.20] | 4698\n",
"( 45.20, 89.40] | 293\n",
"( 89.40, 133.60] | 182\n",
"(133.60, 177.80] | 60\n",
"(177.80, 222.00] | 10"
]
},
"execution_count": 23,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"import mapclassify \n",
"\n",
"ei5 = mapclassify.EqualInterval(fires[\"dur_days\"], k=5)\n",
"ei5"
]
},
{
"cell_type": "markdown",
"id": "42b14f27",
"metadata": {
"slideshow": {
"slide_type": "subslide"
}
},
"source": [
"# Qunatile \n",
"\n",
"* To avoid the potential problem of sparse classes, the quantiles of the distribution can be used to identify the class boundaries. \n",
"* Each class will have approximately observations using the quantile classifier. \n",
"\n",
"## Problems: \n",
"\n",
"* The varying widths of the intervals can be markedly different which can lead to problems of interpretation. \n",
"* There are a large number of duplicate values in the distribution such that the limits for one or more classes become ambiguous."
]
},
{
"cell_type": "code",
"execution_count": 24,
"id": "37dd5677",
"metadata": {
"slideshow": {
"slide_type": "subslide"
}
},
"outputs": [
{
"data": {
"text/plain": [
"Quantiles \n",
"\n",
" Interval Count\n",
"------------------------\n",
"[ 1.00, 1.00] | 1455\n",
"( 1.00, 2.00] | 669\n",
"( 2.00, 5.00] | 1081\n",
"( 5.00, 16.60] | 989\n",
"( 16.60, 222.00] | 1049"
]
},
"execution_count": 24,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"q5 = mapclassify.Quantiles(fires.dur_days, k=5)\n",
"q5"
]
},
{
"cell_type": "markdown",
"id": "a8b58d67",
"metadata": {
"slideshow": {
"slide_type": "subslide"
}
},
"source": [
"# Mean Standard Deviation\n",
"\n",
"* Use sample mean and sample standard deviation to define class boundaries as some distance from the sample mean, with the distance being a multiple of the standard deviation (i.e. +/-1std, +/-2std, +/-3std) \n",
"* This classifier is best used when data is normally distributed or, at least, when the sample mean is a meaningful measure to anchor the classification around. "
]
},
{
"cell_type": "code",
"execution_count": 25,
"id": "428fd273",
"metadata": {
"slideshow": {
"slide_type": "subslide"
}
},
"outputs": [
{
"data": {
"text/plain": [
"StdMean \n",
"\n",
" Interval Count\n",
"------------------------\n",
"( -inf, -43.00] | 0\n",
"(-43.00, -13.86] | 0\n",
"(-13.86, 44.41] | 4690\n",
"( 44.41, 73.55] | 210\n",
"( 73.55, 222.00] | 343"
]
},
"execution_count": 25,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"msd5 = mapclassify.StdMean(fires.dur_days)\n",
"msd5"
]
},
{
"cell_type": "markdown",
"id": "71ff4846",
"metadata": {
"slideshow": {
"slide_type": "subslide"
}
},
"source": [
"# Maximum breaks \n",
"\n",
"* Considering the difference between sorted values. That is, rather than considering a value of the dataset in itself, it looks at how apart each value is from the next one in the sorted sequence. \n",
"* The classifier then places the the break points in between the pairs of values most stretched apart from each other in the entire sequence, proceeding in descending order relative to the size of the breaks\n",
"* Maximum breaks is an appropriate approach when we are interested in making sure observations in each class are separated from those in neighboring classes. As such, it works well in cases where the distribution of values is not unimodal. \n",
"* The algorithm is relatively fast to compute."
]
},
{
"cell_type": "code",
"execution_count": 26,
"id": "68365c40",
"metadata": {
"slideshow": {
"slide_type": "subslide"
}
},
"outputs": [
{
"data": {
"text/plain": [
"MaximumBreaks \n",
"\n",
" Interval Count\n",
"------------------------\n",
"[ 1.00, 173.00] | 5233\n",
"(173.00, 186.50] | 4\n",
"(186.50, 199.50] | 4\n",
"(199.50, 212.00] | 1\n",
"(212.00, 222.00] | 1"
]
},
"execution_count": 26,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"mb5 = mapclassify.MaximumBreaks(fires[\"dur_days\"], k=5)\n",
"mb5"
]
},
{
"cell_type": "markdown",
"id": "2f3106bb",
"metadata": {
"slideshow": {
"slide_type": "subslide"
}
},
"source": [
"# Fisher Jenks \n",
"\n",
"* Dynamic programming approach to minimize the sum of the absolute deviations around class medians\n",
"* Fisher-Jenks is guaranteed to produce an optimal classification for a prespecified number of classes"
]
},
{
"cell_type": "code",
"execution_count": 27,
"id": "e937ba81",
"metadata": {
"slideshow": {
"slide_type": "subslide"
}
},
"outputs": [
{
"data": {
"text/plain": [
"FisherJenks \n",
"\n",
" Interval Count\n",
"------------------------\n",
"[ 1.00, 14.00] | 4109\n",
"( 14.00, 43.00] | 575\n",
"( 43.00, 80.00] | 249\n",
"( 80.00, 124.00] | 225\n",
"(124.00, 222.00] | 85"
]
},
"execution_count": 27,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"fj5 = mapclassify.FisherJenks(fires[\"dur_days\"], k=5)\n",
"fj5"
]
},
{
"cell_type": "markdown",
"id": "ba5b9e69",
"metadata": {
"slideshow": {
"slide_type": "subslide"
}
},
"source": [
"# More classifications \n",
"\n",
"* Box-Plot\n",
"* Head-Tail Breaks\n",
"* Jenks Caspall\n",
"* Max-P"
]
},
{
"cell_type": "code",
"execution_count": 28,
"id": "7c8f7ffc",
"metadata": {
"slideshow": {
"slide_type": "subslide"
}
},
"outputs": [],
"source": [
"fig, ax = plt.subplots(2,2, figsize=(16,8))\n",
"\n",
"##################\n",
"# Equal Interval #\n",
"##################\n",
"tot_by_county_geom.plot(fc='None', ec='k', ax=ax[0,0])\n",
"tot_by_county_geom.plot(\n",
" column=\"INC_NUM\", # Data to plot\n",
" scheme=\"equal_interval\", # Classification scheme\n",
" k=5,\n",
" cmap=\"Reds\", # Color palette\n",
" legend=True, # Add legend\n",
" legend_kwds={\"fmt\": \"{:.0f}\"}, # Remove decimals in legend\n",
" ax=ax[0,0]\n",
")\n",
"ax[0,0].set_axis_off();\n",
"ax[0,0].set_title('Equal Interval Classification', fontsize=12);\n",
"\n",
"#############\n",
"# Quantiles #\n",
"#############\n",
"tot_by_county_geom.plot(fc='None', ec='k', ax=ax[0,1])\n",
"tot_by_county_geom.plot(\n",
" column=\"INC_NUM\", # Data to plot\n",
" scheme=\"quantiles\", # Classification scheme\n",
" k=5,\n",
" cmap=\"Reds\", # Color palette\n",
" legend=True, # Add legend\n",
" legend_kwds={\"fmt\": \"{:.0f}\"}, # Remove decimals in legend\n",
" ax=ax[0,1]\n",
")\n",
"ax[0,1].set_axis_off();\n",
"ax[0,1].set_title('Quantiles Classification', fontsize=12);\n",
"\n",
"##############\n",
"# Mean StDev #\n",
"##############\n",
"tot_by_county_geom.plot(fc='None', ec='k', ax=ax[1,0])\n",
"tot_by_county_geom.plot(\n",
" column=\"INC_NUM\", # Data to plot\n",
" scheme=\"StdMean\", # Classification scheme\n",
" cmap=\"Reds\", # Color palette\n",
" legend=True, # Add legend\n",
" legend_kwds={\"fmt\": \"{:.0f}\"}, # Remove decimals in legend\n",
" ax=ax[1,0]\n",
")\n",
"ax[1,0].set_axis_off();\n",
"ax[1,0].set_title('Mean StDev Classification', fontsize=12);\n",
"\n",
"##########\n",
"# FISHER #\n",
"##########\n",
"tot_by_county_geom.plot(fc='None', ec='k', ax=ax[1,1])\n",
"tot_by_county_geom.plot(\n",
" column=\"INC_NUM\", # Data to plot\n",
" scheme=\"FisherJenks\", # Classification scheme\n",
" cmap=\"Reds\", # Color palette\n",
" legend=True, # Add legend\n",
" legend_kwds={\"fmt\": \"{:.0f}\"}, # Remove decimals in legend\n",
" ax=ax[1,1]\n",
")\n",
"ax[1,1].set_axis_off();\n",
"ax[1,1].set_title('Fisher Jenks Classification', fontsize=12);\n",
"\n",
"fig.tight_layout()\n",
"fig.savefig('classif_compare.png')\n",
"plt.close(fig)"
]
},
{
"cell_type": "code",
"execution_count": 29,
"id": "6646cdf5",
"metadata": {
"slideshow": {
"slide_type": "subslide"
}
},
"outputs": [
{
"data": {
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\n",
"text/plain": [
""
]
},
"execution_count": 29,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"from IPython.display import Image\n",
"Image(filename='classif_compare.png') "
]
},
{
"cell_type": "markdown",
"id": "0f5e48f2",
"metadata": {
"slideshow": {
"slide_type": "slide"
}
},
"source": [
"# Color in Choropleth Mapping \n",
"\n",
"* Classification scheme, symbolization and color scheme will determine the overall effectiveness of the choropleth map\n",
"* The choice of a color scheme for a choropleth map should be based on the type of variable under consideration\n",
"* Three types of numerical attributes: \n",
" * sequential - continuous data \n",
" * diverging - continuous data (equal weight on different parts of the spectrum) \n",
" * qualitative - categorical data "
]
},
{
"cell_type": "code",
"execution_count": 30,
"id": "34e331a3",
"metadata": {
"slideshow": {
"slide_type": "subslide"
}
},
"outputs": [
{
"data": {
"text/plain": [
""
]
},
"execution_count": 30,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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\n",
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