I have the following data:
male 843 female 466 Name: Sex, dtype: int64 I plotted bar plots for the same using countplot from seaborn, and it worked.
But I would like to know what could be its alternative in matplotlib.
I did:
sns.countplot(x = 'Sex', data = complete_data) It gave me:
Say you have this data:
import numpy as np; np.random.seed(42) import pandas as pd import matplotlib.pyplot as plt df = pd.DataFrame({"Sex" : np.random.choice(["male", "female"], size=1310, p=[.65, .35]), "other" : np.random.randint(0,80, size=1310)}) You can plot a countplot in seaborn as
import seaborn as sns sns.countplot(x="Sex", data=df) plt.show() Or you can create a bar plot in pandas
df["Sex"].value_counts().plot.bar() plt.show() Or you can create a bar plot in matplotlib
counts = df["Sex"].value_counts() plt.bar(counts.index, counts.values) plt.show() 