In [1]:

import pandas as pd, numpy as np
import hvplot.pandas
import seaborn as sns

In [14]:

dfLiving = pd.read_csv('data/CombinedLivingArangDf.csv')
dfLiving = dfLiving.set_index('Year')
dfLiving = dfLiving.drop(labels='Count', axis=1)

In [15]:

dfLiving.hvplot(value_label='Percent of Age Group')

Out[15]:

In [ ]:

In [16]:

dfPenguins = sns.load_dataset("penguins")

In [17]:

dfPenguins.hvplot.bivariate('bill_length_mm', 'bill_depth_mm', width=500, height=400, legend=False) *\
dfPenguins.hvplot.scatter('bill_length_mm', 'bill_depth_mm', color='black', size=15, legend=False) +\
dfPenguins.hvplot.table(['bill_length_mm', 'bill_depth_mm'], width=250, height=350)

Out[17]:

In [ ]:

In [19]:

import xarray as xr, cartopy.crs as ccrs
import hvplot.xarray

air_data = xr.tutorial.open_dataset('air_temperature').load()

In [20]:

proj = ccrs.Orthographic(-90, 30)

air_data.air.isel(time=slice(0, 9, 3)).hvplot.quadmesh(
    'lon', 'lat', projection=proj, project=True, global_extent=True, 
    cmap='viridis', rasterize=True, dynamic=False, coastline=True, 
    frame_width=500)

Out[20]:

In [ ]:

In [26]:

import hvplot.streamz
from streamz.dataframe import Random

In [27]:

stream_df = Random(freq='10ms')

In [29]:

stream_df.hvplot(backlog=80, height=300, width=400) +\
stream_df.hvplot.hexbin(x='x', y='z', backlog=1600, height=300, width=400)

Out[29]:

In [ ]:

In [21]:

import networkx as nx
import hvplot.networkx as hvnx

In [22]:

characters = ["R2-D2",
                "CHEWBACCA",
                "C-3PO",
                "LUKE",
                "DARTH VADER",
                "CAMIE",
                "BIGGS",
                "LEIA",
                "BERU",
                "OWEN",
                "OBI-WAN",
                "MOTTI",
                "TARKIN",
                "HAN",
                "DODONNA",
                "GOLD LEADER",
                "WEDGE",
                "RED LEADER",
                "RED TEN"]


edges = [("CHEWBACCA", "R2-D2"),
        ("C-3PO", "R2-D2"),
        ("BERU", "R2-D2"),
        ("LUKE", "R2-D2"),
        ("OWEN", "R2-D2"),
        ("OBI-WAN", "R2-D2"),
        ("LEIA", "R2-D2"),
        ("BIGGS", "R2-D2"),
        ("HAN", "R2-D2"),
        ("CHEWBACCA", "OBI-WAN"),
        ("C-3PO", "CHEWBACCA"),
        ("CHEWBACCA", "LUKE"),
        ("CHEWBACCA", "HAN"),
        ("CHEWBACCA", "LEIA"),
        ("CAMIE", "LUKE"),
        ("BIGGS", "CAMIE"),
        ("BIGGS", "LUKE"),
        ("DARTH VADER", "LEIA"),
        ("BERU", "LUKE"),
        ("BERU", "OWEN"),
        ("BERU", "C-3PO"),
        ("LUKE", "OWEN"),
        ("C-3PO", "LUKE"),
        ("C-3PO", "OWEN"),
        ("C-3PO", "LEIA"),
        ("LEIA", "LUKE"),
        ("BERU", "LEIA"),
        ("LUKE", "OBI-WAN"),
        ("C-3PO", "OBI-WAN"),
        ("LEIA", "OBI-WAN"),
        ("MOTTI", "TARKIN"),
        ("DARTH VADER", "MOTTI"),
        ("DARTH VADER", "TARKIN"),
        ("HAN", "OBI-WAN"),
        ("HAN", "LUKE"),
        ("C-3PO", "HAN"),
        ("LEIA", "MOTTI"),
        ("LEIA", "TARKIN"),
        ("HAN", "LEIA"),
        ("DARTH VADER", "OBI-WAN"),
        ("DODONNA", "GOLD LEADER"),
        ("DODONNA", "WEDGE"),
        ("DODONNA", "LUKE"),
        ("GOLD LEADER", "WEDGE"),
        ("GOLD LEADER", "LUKE"),
        ("LUKE", "WEDGE"),
        ("BIGGS", "LEIA"),
        ("LEIA", "RED LEADER"),
        ("LUKE", "RED LEADER"),
        ("BIGGS", "RED LEADER"),
        ("BIGGS", "C-3PO"),
        ("C-3PO", "RED LEADER"),
        ("RED LEADER", "WEDGE"),
        ("GOLD LEADER", "RED LEADER"),
        ("BIGGS", "WEDGE"),
        ("RED LEADER", "RED TEN"),
        ("BIGGS", "GOLD LEADER"),
        ("LUKE", "RED TEN")]

G = nx.Graph()


G.add_nodes_from(characters)
G.add_edges_from(edges)

In [23]:

pos = nx.circular_layout(G)
hvnx.draw_circular(G, labels="index")

Out[23]: