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samples/04_gis_analysts_data_scientists/finding_a_new_home.ipynb

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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"5) Read the **Crestline3BdrmAveSellingPrice** excel data from local `datapath`, and restructure it as a Dataframe."
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"3) Read the **Crestline3BdrmAveSellingPrice** excel data from local `datapath`, and restructure it as a Dataframe."
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"6) Create a graph using `matplotlib` library to show how average home prices have changed since they bought their home."
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"4) Create a graph using `matplotlib` library to show how average home prices have changed since they bought their home."
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"7) Determine an appropriate selling price based on home sales trends as follows:\n",
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"5) Determine an appropriate selling price based on home sales trends as follows:\n",
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"\n",
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"> a) Determine the current average selling price and the average selling price when they bought their home. Divide the current average price by the beginning average price to see how much homes in their ZIP Code have appreciated or depreciated. When Mark and Lisa bought their home in December of 2007, 3-bedroom homes were selling for \\$276,617. "
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]
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"6) Create a map that displays the overlap by adding both `hlth_lyr` (classified by **MarketHealthIndex** field) and `drive_time_lyr`."
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"7) Create a map that displays the overlap by adding both `hlth_lyr` (classified by **MarketHealthIndex** field) and `drive_time_lyr`."
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"7) Create a map that displays the overlap by adding both `hlth_lyr` (classified by **ZHVI** field) and `drive_time_lyr`."
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"8) Create a map that displays the overlap by adding both `hlth_lyr` (classified by **ZHVI** field) and `drive_time_lyr`."
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"8) Create a map that displays the overlap by adding both `hlth_lyr` (classified by **ForecastYoYPctChange** field) and `drive_time_lyr`."
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"9) Create a map that displays the overlap by adding both `hlth_lyr` (classified by **ForecastYoYPctChange** field) and `drive_time_lyr`."
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]
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},
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{
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.11.0"
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"version": "3.11.11"
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}
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},
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"nbformat": 4,

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