How to generate BAR plot using pandas DataFrame?
This recipe helps you generate BAR plot using pandas DataFrame
Recipe Objective
visualizing a dataset give us a overall view of the data. It gives various statistical description about the data.
So this is the recipe on how we can generate BAR plot using pandas DataFrame. .
Step 1 - Importing Library
import pandas as pd
import matplotlib.pyplot as plt
import numpy as np
We have only imported pandas, numpy and matplotlib.pyplot which is needed.
Step 2 - Creating DataFrame
We have created a Dictionary and passed it through pd.DataFrame to create dataframe with different features.
raw_data = {"first_name": ["Jason", "Molly", "Tina", "Jake", "Amy"],
"pre_score": [4, 24, 31, 2, 3],
"mid_score": [25, 94, 57, 62, 70],
"post_score": [5, 43, 23, 23, 51]}
df = pd.DataFrame(raw_data, columns = ["first_name", "pre_score", "mid_score", "post_score"])
print(df)
Step 3 - Creating Bar Plot
We have done various steps to plot bar graph. First we have assigned labels to the bar, then the y and horizontal position of the the bar. Bar graph is ploted by the function plt.barh and finally labelling the x, y axis and the graph.
Molly = df.ix[1, 1:]
Tina = df.ix[2, 1:]
bar_labels = ["Pre Score", "Mid Score", "Post Score"]
plt.figure(figsize=(8,6))
y_pos = np.arange(len(Molly))
y_pos = [x for x in y_pos]
plt.yticks(y_pos, bar_labels, fontsize=10)
plt.barh(y_pos, Molly, align="center", alpha=0.4, color="#263F13")
plt.barh(y_pos, -Tina, align="center", alpha=0.4, color="#77A61D")
plt.xlabel("Tina"s Score: Light Green. Molly"s Score: Dark Green")
plt.title("Comparison of Molly and Tina"s Score")
plt.ylim([-1,len(Molly)+0.1])
plt.xlim([-max(Tina)-10, max(Tina)+10])
plt.grid(); plt.show()
So the output comes as
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