viz.py

# importing the required libarary
import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt

df = pd.read_excel("online_retail_II.xlsx")

df.head()

#Bar chart visualisation
mask_df = df["Country"].value_counts().head(10)
fig1 = plt.figure(figsize=(12, 10))
plt.bar(x = mask_df.index, height=mask_df, color="sienna")
plt.xlabel("Country")
plt.ylabel("Counts")
plt.title("Numbers of Orders from Countries Over the Years")
plt.xticks(rotation=45);

#Histogram visualization
fig2 = plt.figure(figsize=(12, 10))
sns.histplot(df["InvoiceDate"], color="darkslategrey", bins=50)
plt.title("Distribution of the Invoice Date");

# import comet_ml at the top of your file
from comet_ml import Experiment

# Create an experiment with your api key
experiment = Experiment(
    api_key = "your API key",
    project_name = "viz",
    workspace="zenunicorn",
)

#logging the viz to comet
experiment.log_figure(figure_name="Matplotlib Viz", figure=fig1)
experiment.log_figure(figure_name= "Seaborn Viz", figure=fig2)

#always end your experiment
experiment.end()

@zenUnicorn