Fancy Plots using Plotly

• This is a collection of simple plots using the plotly library.
• It consists of elegant color schemes and easy to ready adjustable fonts.
• The reason for using plotly is that it allows for HTML plots that can be scaled and zoomed after plotting.

Installation

We need the plotly-express and kaleido library.

Conda

conda install -c plotly plotly_express==0.4.0
conda install -c conda-forge python-kaleido

Pip

pip install plotly_express==0.4.0
pip install kaleido

Line Plots

CSV Data:

animal,age,cuteness
cat,1,5
cat,2,8
cat,3,12
cat,4,15
cat,5,14
cat,6,15
cat,7,16
cat,8,18
cat,9,17
cat,10,10
dog,1,12
dog,2,14
dog,3,18
dog,4,20
dog,5,19
dog,6,17
dog,7,14
dog,8,9
dog,9,8
dog,10,6

Code:

import plotly.express as px
import pandas as pd
from tqdm import tqdm
PLOTS_DIR = "./plots"
PLOT_NAME = "cat_v_dog"
PLOT_TYPES = ["svg", "png", "html", "pdf", "jpeg"]
FIG_DIR = PLOTS_DIR + "/" + PLOT_NAME
!mkdir -p $FIG_DIR

Plot Size
PLOT_WIDTH = 800
PLOT_HEIGHT = 300


df = pd.read_csv('./data/sample.csv')
fig = px.line(df, x="age", y="cuteness", color="animal")
fig.update_layout(

   title="Cat vs Dog Cuteness",
   xaxis_title="Animal's Age",
   yaxis_title="Cuteness Rating",
   legend_title="Animal",
   font=dict(
       family="Courier New, monospace",
       size=14,
       color="RebeccaPurple"
   )

)
fig.update_layout(

   autosize=True,
   width=PLOT_WIDTH,
   height=PLOT_HEIGHT,
   margin=dict(
       l=50,
       r=50,
       b=50,
       t=50,
       pad=4
   ),
   legend=dict(
       yanchor="top",
       y=0.999,
       xanchor="left",
       x=0.001)

)
fig.show()

Save Plot
for i in tqdm(range(len(PLOT_TYPES))):

   if PLOT_TYPES[i] == "html":
       fig.write_html(FIG_DIR + "/" + PLOT_NAME + "." + PLOT_TYPES[i])
   else:

        fig.write_image(FIG_DIR + "/" + PLOT_NAME + "." + PLOT_TYPES[i], scale=5)

import plotly.express as px
import pandas as pd
from tqdm import tqdm

PLOTS_DIR = "./plots"
PLOT_NAME = "cat_v_dog"
PLOT_TYPES = ["svg", "png", "html", "pdf", "jpeg"]
FIG_DIR = PLOTS_DIR + "/" + PLOT_NAME
!mkdir -p $FIG_DIR

# Plot Size
PLOT_WIDTH = 800
PLOT_HEIGHT = 300


df = pd.read_csv('./data/sample.csv')
fig = px.line(df, x="age", y="cuteness", color="animal")
fig.update_layout(
 title="Cat vs Dog Cuteness",
 xaxis_title="Animal's Age",
 yaxis_title="Cuteness Rating",
 legend_title="Animal",
 font=dict(
  family="Courier New, monospace",
  size=14,
  color="RebeccaPurple"
  )
)

fig.update_layout(
 autosize=True,
 width=PLOT_WIDTH,
 height=PLOT_HEIGHT,
 margin=dict(
  l=50,
  r=50,
  b=50,
  t=50,
  pad=4
  ),
  legend=dict(
  yanchor="top",
  y=0.999,
  xanchor="left",
  x=0.001)
)

fig.show()
# Save Plot
for i in tqdm(range(len(PLOT_TYPES))):
 if PLOT_TYPES[i] == "html":
  fig.write_html(FIG_DIR + "/" + PLOT_NAME + "." + PLOT_TYPES[i])
 else:
  fig.write_image(FIG_DIR + "/" + PLOT_NAME + "." + PLOT_TYPES[i], scale=5)

import plotly.express as px
import pandas as pd
from tqdm import tqdm

PLOTS_DIR = "./plots"
PLOT_NAME = "cat_v_dog"
PLOT_TYPES = ["svg", "png", "html", "pdf", "jpeg"]
FIG_DIR = PLOTS_DIR + "/" + PLOT_NAME
!mkdir -p $FIG_DIR

# Plot Size
PLOT_WIDTH = 800
PLOT_HEIGHT = 300


df = pd.read_csv('./data/sample.csv')
fig = px.line(df, x="age", y="cuteness", color="animal")
fig.update_layout(
    title="Cat vs Dog Cuteness",
    xaxis_title="Animal's Age",
    yaxis_title="Cuteness Rating",
    legend_title="Animal",
    font=dict(
        family="Courier New, monospace",
        size=14,
        color="RebeccaPurple"
    )
)

fig.update_layout(
    autosize=True,
    width=PLOT_WIDTH,
    height=PLOT_HEIGHT,
    margin=dict(
        l=50,
        r=50,
        b=50,
        t=50,
        pad=4
    ),
    legend=dict(
        yanchor="top",
        y=0.999,
        xanchor="left",
        x=0.001)
)

fig.show()
# Save Plot
for i in tqdm(range(len(PLOT_TYPES))):
    if PLOT_TYPES[i] == "html":
        fig.write_html(FIG_DIR + "/" + PLOT_NAME + "." + PLOT_TYPES[i])
    else:
        fig.write_image(FIG_DIR + "/" + PLOT_NAME + "." + PLOT_TYPES[i], scale=5)

Output: