#!/usr/bin/env python
# coding: utf-8

# # Plotly Express Gallery
# 
# Plotly Express is a terse, consistent, high-level wrapper around [Plotly.py](https://plot.ly/python) for rapid data exploration and figure generation.
# 
# This notebook demonstrates various `plotly_express` features. [Reference documentation](https://plotly.github.io/plotly_express/plotly_express/) and a [step by step walkthrough notebook](https://nbviewer.jupyter.org/github/plotly/plotly_express/blob/master/walkthrough.ipynb) are also available.
# 
# You can also read our [Medium announcement article](https://medium.com/@plotlygraphs/introducing-plotly-express-808df010143d) for more information on this library.

# ## A single import

# In[1]:


import plotly_express as px


# ## Built-in sample datasets

# In[2]:


print(px.data.iris.__doc__)
iris = px.data.iris()


# In[3]:


tips = px.data.tips()
gapminder = px.data.gapminder()
election = px.data.election()
wind = px.data.wind()
carshare = px.data.carshare()


# ## Scatter and Line plots

# In[4]:


px.scatter(iris, x="sepal_width", y="sepal_length")


# In[5]:


px.scatter(iris, x="sepal_width", y="sepal_length", color="species")


# In[6]:


px.scatter(iris, x="sepal_width", y="sepal_length", color="species", marginal_y="violin", marginal_x="rug")


# In[7]:


px.scatter(iris, x="sepal_width", y="sepal_length", color="species", marginal_y="violin", 
           marginal_x="box", trendline="ols")


# In[8]:


iris["e"] = iris["sepal_width"]/100
px.scatter(iris, x="sepal_width", y="sepal_length", color="species", error_x="e", error_y="e")


# In[9]:


del iris["e"]


# In[10]:


px.scatter(tips, x="total_bill", y="tip", facet_row="time", facet_col="day", color="smoker", trendline="ols",
          category_orders={"day": ["Thur", "Fri", "Sat", "Sun"], "time": ["Lunch", "Dinner"]})


# In[11]:


px.scatter_matrix(iris)


# In[12]:


px.scatter_matrix(iris, dimensions=["sepal_width", "sepal_length", "petal_width", "petal_length"], color="species")


# In[13]:


px.parallel_coordinates(iris, color="species_id", labels={"species_id": "Species",
                  "sepal_width": "Sepal Width", "sepal_length": "Sepal Length", 
                  "petal_width": "Petal Width", "petal_length": "Petal Length", },
                    color_continuous_scale=px.colors.diverging.Tealrose, color_continuous_midpoint=2)


# In[14]:


px.parallel_categories(tips, color="size", color_continuous_scale=px.colors.sequential.Inferno)


# In[15]:


px.scatter(tips, x="total_bill", y="tip", color="size", facet_col="sex",
           color_continuous_scale=px.colors.sequential.Viridis, render_mode="webgl")


# In[16]:


px.scatter(gapminder.query("year==2007"), x="gdpPercap", y="lifeExp", size="pop", color="continent", 
           hover_name="country", log_x=True, size_max=60)


# In[17]:


px.scatter(gapminder, x="gdpPercap", y="lifeExp", animation_frame="year", animation_group="country",
           size="pop", color="continent", hover_name="country", facet_col="continent",
           log_x=True, size_max=45, range_x=[100,100000], range_y=[25,90])


# In[18]:


px.line(gapminder, x="year", y="lifeExp", color="continent", line_group="country", hover_name="country", 
        line_shape="spline")


# ## Visualize Distributions

# In[19]:


px.density_contour(iris, x="sepal_width", y="sepal_length")


# In[20]:


px.density_contour(iris, x="sepal_width", y="sepal_length", color="species")


# In[21]:


px.density_contour(tips, x="total_bill", y="tip", color="day", facet_col="day")


# In[22]:


px.bar(tips, x="total_bill", y="sex", orientation="h", color="smoker")


# In[23]:


px.histogram(tips, x="total_bill", y="tip")


# In[24]:


px.histogram(tips, x="sex", y="tip", color="smoker", facet_row="day", orientation="v", barmode="group",
      category_orders={"day": ["Thur", "Fri", "Sat", "Sun"]})


# In[25]:


px.histogram(tips, x="total_bill", y="tip", histfunc="sum", color="smoker")


# In[26]:


px.histogram(tips, x="total_bill", color="smoker", facet_row="day", facet_col="time")


# In[27]:


px.box(tips, x="total_bill", y="day", orientation="h", color="smoker", notched=True,
       category_orders={"day": ["Thur", "Fri", "Sat", "Sun"]})


# In[28]:


px.violin(tips, y="tip", x="smoker", color="sex", box=True, points="all")


# In[29]:


px.violin(tips, y="tip", x="sex", color="smoker", facet_row="day")


# In[30]:


px.violin(tips, y="tip", x="sex", color="smoker", facet_col="day", facet_row="time")


# In[31]:


px.box(tips, y="tip", x="sex")


# In[32]:


px.box(tips, y="tip", x="sex", color="smoker", facet_col="day", facet_row="time", 
       category_orders={"day": ["Thur", "Fri", "Sat", "Sun"], "time": ["Lunch", "Dinner"]})


# In[33]:


px.box(tips, x="tip", y="sex", color="smoker", facet_col="day", facet_row="time", orientation="h")


# ## Ternary Coordinates

# In[34]:


px.scatter_ternary(election, a="Joly", b="Coderre", c="Bergeron", color="winner", size="total", hover_name="district",
                   symbol="result", 
                   size_max=15, color_discrete_map = {"Joly": "blue", "Bergeron": "green", "Coderre":"red"}
                  )


# In[35]:


px.line_ternary(election, a="Joly", b="Coderre", c="Bergeron", color="winner", line_dash="winner")


# ## 3D Coordinates

# In[36]:


px.scatter_3d(election, x="Joly", y="Coderre", z="Bergeron", color="winner", size="total", hover_name="district",
                  symbol="result", color_discrete_map = {"Joly": "blue", "Bergeron": "green", "Coderre":"red"})


# In[37]:


px.line_3d(election, x="Joly", y="Coderre", z="Bergeron", color="winner", line_dash="winner")


# ## Polar Coordinates

# In[38]:


px.scatter_polar(wind, r="value", theta="direction", color="strength", symbol="strength",
            color_discrete_sequence=px.colors.sequential.Plotly[-2::-1])


# In[39]:


px.line_polar(wind, r="value", theta="direction", color="strength", line_close=True,
            color_discrete_sequence=px.colors.sequential.Plotly[-2::-1])


# In[40]:


px.bar_polar(wind, r="value", theta="direction", color="strength", template="plotly_dark",
            color_discrete_sequence= px.colors.sequential.Plotly[-2::-1])


# ## Maps

# In[41]:


px.set_mapbox_access_token(open(".mapbox_token").read())
px.scatter_mapbox(carshare, lat="centroid_lat", lon="centroid_lon", color="peak_hour", size="car_hours", 
                  color_continuous_scale=px.colors.cyclical.IceFire, size_max=15, zoom=10)


# In[42]:


px.set_mapbox_access_token(open(".mapbox_token").read())
px.line_mapbox(carshare, lat="centroid_lat", lon="centroid_lon", color="peak_hour")


# In[43]:


px.scatter_geo(gapminder, locations="iso_alpha", color="continent", hover_name="country", size="pop", 
               animation_frame="year", projection="natural earth")


# In[44]:


px.line_geo(gapminder.query("year==2007"), locations="iso_alpha", color="continent", projection="orthographic")


# In[45]:


px.choropleth(gapminder, locations="iso_alpha", color="lifeExp", hover_name="country", animation_frame="year",
             color_continuous_scale=px.colors.sequential.Plasma)


# ## Built-in Color Scales and Sequences (and a way to see them!)

# In[46]:


px.colors.qualitative.swatches()


# In[47]:


px.colors.sequential.swatches()


# In[48]:


px.colors.diverging.swatches()


# In[49]:


px.colors.cyclical.swatches()


# In[50]:


px.colors.colorbrewer.swatches()


# In[51]:


px.colors.cmocean.swatches()


# In[52]:


px.colors.carto.swatches()


# # Next steps
# 
# Phew, you've made it this far! If you want to use Plotly Express yourself, just `pip install plotly_express` to install it and head on over to our [reference documentation](https://plotly.github.io/plotly_express/plotly_express/) or just copy-paste from the examples above!