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Python Articles
Page 348 of 855
Python Pandas - Draw swarms of observations on top of a violin plot with Seaborn
A violin plot shows the distribution of data across categories, while a swarm plot displays individual data points without overlap. Combining them creates a powerful visualization that shows both distribution shape and individual observations. Creating Sample Data Let's create sample cricket data to demonstrate this visualization ? import seaborn as sb import pandas as pd import matplotlib.pyplot as plt import numpy as np # Create sample cricket data np.random.seed(42) data = { 'Role': ['Batsman'] * 20 + ['Bowler'] * 20 + ['All-rounder'] * 15, 'Matches': ( ...
Read MorePython - Read csv file with Pandas without header?
To read a CSV file without headers in Pandas, use the header=None parameter in the read_csv() method. This treats the first row as data rather than column names. Default CSV Reading (With Header) By default, Pandas treats the first row as column headers − import pandas as pd # Sample CSV data (normally you'd read from a file) csv_data = """Car, Reg_Price, Units BMW, 2500, 100 Lexus, 3500, 80 Audi, 2500, 120 Jaguar, 2000, 70 Mustang, 2500, 110""" # Save to a temporary file for demonstration with open('sample.csv', 'w') as f: ...
Read MoreRename column name with an index number of the CSV file in Pandas
Pandas provides the columns.values attribute to rename column names by index position. This approach lets you modify column names directly using their integer index instead of their current names. Creating Sample Data Let's create a sample DataFrame to demonstrate column renaming ? import pandas as pd # Create sample data similar to CSV format data = { 'Car': ['BMW', 'Lexus', 'Audi', 'Jaguar', 'Mustang'], 'Reg_Price': [2500, 3500, 2500, 2000, 2500], 'Units': [100, 80, 120, 70, 110] } dataFrame = pd.DataFrame(data) print("Original DataFrame:") print(dataFrame) ...
Read MoreSelect rows that contain specific text using Pandas
To select rows that contain specific text in Pandas, use the str.contains() method. This is useful for filtering DataFrames based on text patterns or substrings within columns. Basic Syntax The basic syntax for selecting rows with specific text is ? df = df[df['column_name'].str.contains('text')] Example with Sample Data Let's create a sample DataFrame and select rows containing "BMW" ? import pandas as pd # Creating a sample DataFrame data = { 'Car': ['Audi', 'Porsche', 'RollsRoyce', 'BMW', 'Mercedes', 'Lamborghini', 'Audi', 'Mercedes', 'Lamborghini'], 'Place': ['Bangalore', ...
Read MorePython - Select multiple columns from a Pandas dataframe
Selecting multiple columns from a Pandas DataFrame is a common operation in data analysis. You can select specific columns using square brackets with column names to create a subset of your data. Basic Syntax To select multiple columns, use double square brackets with a list of column names ? # Syntax: df[['column1', 'column2', 'column3']] Creating Sample Data Let's create a sample DataFrame to demonstrate column selection ? import pandas as pd # Create sample sales data data = { 'Car': ['BMW', 'Lexus', 'Audi', 'Jaguar', 'Mustang'], ...
Read MorePython Pandas - Select a subset of rows from a dataframe
Selecting subsets of rows from a DataFrame is a fundamental operation in Pandas. You can filter rows using boolean conditions to extract data that meets specific criteria. Basic Row Selection with Conditions Use boolean indexing with square brackets to filter rows. The condition returns a boolean Series that selects matching rows ? import pandas as pd # Create sample data data = { 'Car': ['BMW', 'Lexus', 'Audi', 'Jaguar', 'Mustang'], 'Reg_Price': [2500, 3500, 2500, 2000, 2500], 'Units': [100, 80, 120, 70, 110] } df ...
Read MorePython - How to select a subset of a Pandas DataFrame
A Pandas DataFrame is a two-dimensional data structure that allows you to select specific subsets of data. You can select single columns, multiple columns, or rows based on conditions using various methods. Creating Sample Data Let's create a sample DataFrame to demonstrate subset selection ? import pandas as pd # Create sample data data = { 'Car': ['BMW', 'Lexus', 'Audi', 'Jaguar', 'Mustang'], 'Reg_Price': [2500, 3500, 2500, 2000, 2500], 'Units': [100, 80, 120, 70, 110] } dataFrame = pd.DataFrame(data) print("Original DataFrame:") print(dataFrame) ...
Read MorePython - How to plot a Pandas DataFrame in a Bar Graph
A Pandas DataFrame can be easily visualized as a bar graph using the built-in plot() method. This is useful for comparing categorical data and displaying numerical relationships. Sample Dataset Let's create a sample DataFrame with car sales data ? import pandas as pd import matplotlib.pyplot as plt # Create sample data data = { 'Car': ['BMW', 'Lexus', 'Audi', 'Jaguar', 'Mustang'], 'Reg_Price': [2000, 1500, 1500, 2000, 1500] } dataFrame = pd.DataFrame(data) print(dataFrame) Car Reg_Price 0 ...
Read MorePython Pandas - Plot multiple data columns in a DataFrame?
To plot multiple columns from a DataFrame, we use the plot() method with specific column selection. This is useful for comparing different data series visually using various chart types like bar graphs, line plots, and scatter plots. Import Required Libraries First, import pandas and matplotlib for data manipulation and plotting − import pandas as pd import matplotlib.pyplot as plt Creating Sample Data Let's create a DataFrame with cricket team rankings data − import pandas as pd import matplotlib.pyplot as plt # Sample cricket team data data = [["Australia", 2500, 85], ...
Read MorePython Pandas - Draw a Bar Plot and use median as the estimate of central tendency
A bar plot in Seaborn displays point estimates and confidence intervals as rectangular bars. You can use the estimator parameter in seaborn.barplot() to set median as the measure of central tendency instead of the default mean. Required Libraries Import the necessary libraries for creating bar plots with median estimation ? import seaborn as sns import pandas as pd import matplotlib.pyplot as plt import numpy as np Creating Sample Data Let's create sample cricket data to demonstrate median estimation in bar plots ? import seaborn as sns import pandas as pd import ...
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