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Fancy Plots using Plotly

Revision as of 11:48, 18 February 2022 by Kaustubh (talk | contribs) (Line plots added)


  • 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

  1. 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()

  1. 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:

Cat vs dog cuteness.png

Scatter Plots


Bar Plots


Radar Plots


Bubble Charts


Box Plots


2D Histograms