Get the xls data for this tutorial from: depaul.edu. This dataset contains a list of US presidents, associated parties,profession and more.
Related course
Data Analysis in Python with Pandas
Beautiful Plots with Pandas
We can plot data of this large excel file with a few lines of code. We select the column “Occupation” for this demonstration using:
df['Occupation']. |
Full code:
from pandas import DataFrame, read_csv import matplotlib.pyplot as plt import pandas as pd file = r'data/Presidents.xls' df = pd.read_excel(file) # plot data colors = ['yellowgreen', 'gold', 'lightskyblue', 'lightcoral','red','green','blue','orange','white','brown'] df['Occupation'].value_counts().plot(kind='pie',title='Occupation by President',colors=colors) plt.show() |
Data cleaning and plotting
We can also plot the popularity by president. Before we do that, we need to clean some data:
Some of the cells do not contain numerical values, we can either remove them or replace them:
#df = df.replace('NA()',0) df = df[df['% popular'] != 'NA()'] |
To plot the popularity:
from pandas import DataFrame, read_csv import matplotlib.pyplot as plt import pandas as pd file = r'data/Presidents.xls' df = pd.read_excel(file) # plot data #df = df.replace('NA()',0) df = df[df['% popular'] != 'NA()'] print( df['% popular'] ) df['% popular'].plot(kind='hist', bins=8, title='Popularity by President', facecolor='blue', alpha=0.5, normed=1) plt.show() |
