# importing the required library
import seaborn as sns
import matplotlib.pyplot as plt
# read a titanic.csv file
# from seaborn library
df = sns.load_dataset('titanic')
# class v / s fare barplot
sns.barplot(x = 'class', y = 'fare', hue = 'sex', data = df)
# Show the plot
plt.show()>>> ax = sns.countplot(x="who", data=titanic, palette="Set3")
# importing the required library
import seaborn as sns
import matplotlib.pyplot as plt
# read a titanic.csv file
# from seaborn library
df = sns.load_dataset('titanic')
# class v / s fare barplot
sns.barplot(x = 'class', y = 'fare', data = df)
# Show the plot
plt.show()# instead of seaborn use plt.bar
import matplotlib.pyplot as plt
import seaborn as sns
# Load the example car crash dataset
crashes = sns.load_dataset("car_crashes").sort_values("total", ascending=False)
# states of interest
txcahi = crashes[crashes['abbrev'].isin(['TX','CA','HI'])]
# Plot the total crashes
f, ax = plt.subplots(figsize=(10, 5))
plt.xticks(rotation=90, fontsize=10)
plt.bar(height="total", x="abbrev", data=crashes, label="Total", color="lightgray")
plt.bar(height="total", x="abbrev", data=txcahi, label="Total", color="red")
sns.despine(left=True, bottom=True)