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docs-markdown/utils.md

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+## row_to_geojson
+Convert a pandas dataframe row to a geojson format object. Converts all datetimes to epoch seconds.
+
+### Params
+**row_to_geojson**(_row, lon, lat_)
+
+Parameter | Description
+--|--
+row | Pandas dataframe row.
+lon | Name of dataframe column containing latitude values.
+lat | Name of dataframe column containing longitude values.
+
+## df_to_geojson
+Serialize a Pandas dataframe to a geojson format Python dictionary
+
+### Params
+**df_to_geojson**(_df, properties=None, lat='lat', lon='lon', precision=None, filename=None_)
+
+Parameter | Description
+--|--
+df | Pandas dataframe
+properties | List of dataframe columns to include as object properties. Does not accept lat or lon as a valid property.
+lon | Name of dataframe column containing latitude values.
+lat | Name of dataframe column containing longitude values.
+precision | Accuracy of lat/lon values. Values are rounded to the desired precision.
+filename | Name of file for writing geojson data. Data is stored as an object if filename is not provided.
+
+### Usage
+
+```python
+import pandas as pd
+from mapboxgl.utils import *
+
+# Load gage data from sample csv
+data_url = "https://raw.githubusercontent.com/mapbox/mapboxgl-jupyter/master/examples/cdec.csv"
+df = pd.read_csv(data_url)
+
+# Convert Elevation series to float
+df['Elevation (feet)'] = df['Elevation (feet)'].astype(float)
+
+# Clean up by dropping null rows
+df.dropna(axis=1, how='all', inplace=True)
+
+# Create geojson data object
+df_to_geojson(
+      df.fillna(''),
+      filename="cdec.geojson",
+      properties=['CDEC ID', 'CNRFC ID', 'Gage Type', 'Elevation (feet)'],
+      precision=4
+)
+>>> {'feature_count': 2353, 'filename': 'cdec.geojson', 'type': 'file'}
+```
+
+## scale_between
+Scale a min and max value to equal interval domain with numStops discrete values
+
+### Params
+**scale_between**(_minval, maxval, numStops_)
+
+Parameter | Description
+--|--
+minval | minimum value
+maxval | maximum value
+numStops | number of intervals
+
+## create_radius_stops
+Convert a data breaks into a radius ramp
+
+### Params
+**create_radius_stops**(_breaks, min_radius, max_radius_)
+
+Parameter | Description
+--|--
+breaks | List of float values
+min_radius | Minimum radius value
+max_radius | Maximum radius value
+
+## create_weight_stops
+Convert data breaks into a heatmap-weight ramp
+
+### Params
+**create_weight_stops**(_breaks_)
+
+Parameter | Description
+--|--
+breaks | List of float values
+
+## create_color_stops
+Convert a list of breaks into color stops using colors from colorBrewer.
+
+### Params
+**create_color_stops**(_breaks, colors='RdYlGn'_)
+
+Parameter | Description
+--|--
+breaks | List of float values
+colors | String value for color ramp.
+
+### Color Options
+
+**Multi-Hue** | **Single Hue** | **Diverging** | **Qualitative**
+--|--|--|--
+YlGn | Blues | BrBG | Accent
+YlGnB | Greens | PiYG | Dark2
+BuGn | Greys | PRGn | Paired
+BuPu | Oranges | PuOr | Pastel1
+GnBu | Purples | RdBu | Pastel2
+OrRd | Reds | RdGy | Set1
+PuBu |  | RdYlBu | Set2
+PuBuGn |  | RdYlGn | Set3
+PuRd |  | Spectral |
+RdPu |  |  |
+YlGn |  |  |
+YlOrBr |  |  |
+YlOrRd |  |  |
+
+### Usage
+```python
+from mapboxgl.utils import *
+import pandas as pd
+
+# Load data from sample csv
+data_url = 'https://raw.githubusercontent.com/mapbox/mapboxgl-jupyter/master/examples/points.csv'
+df = pd.read_csv(data_url)
+
+# Generate a new data domain breaks and a new color palette from colorBrewer2
+color_breaks = [0,10,100,1000,10000]
+color_stops = create_color_stops(color_breaks, colors='YlOrRd')
+```