Data Structure
Networking
RDBMS
Operating System
Java
MS Excel
iOS
HTML
CSS
Android
Python
C Programming
C++
C#
MongoDB
MySQL
Javascript
PHP
Swarm Plot in Seaborn is used to draw a categorical scatterplot with non-overlapping points. The seaborn.swarmplot() is used for this. Group the swarms by a categorical variable by simply setting it as one of the x and y coordinates.Let’s say the following is our dataset in the form of a CSV file − Cricketers2.csvAt first, import the required libraries −import seaborn as sb import pandas as pd import matplotlib.pyplot as pltLoad data from a CSV file into a Pandas DataFrame −dataFrame = pd.read_csv("C:\Users\amit_\Desktop\Cricketers2.csv") Group the swarms by a categorical variable −sb.swarmplot(x = dataFrame["Role"], y = dataFrame["Age"])ExampleFollowing is the code −import ... Read More
Swarm Plot in Seaborn is used to draw a categorical scatterplot with non-overlapping points. The seaborn.swarmplot() is used for this. Let’s say the following is our dataset in the form of a CSV file − Cricketers2.csvAt first, import the required libraries −import seaborn as sb import pandas as pd import matplotlib.pyplot as pltLoad data from a CSV file into a Pandas DataFrame −dataFrame = pd.read_csv("C:\Users\amit_\Desktop\Cricketers2.csv") Plotting swarm plot with the “Matches” column −sb.swarmplot(x = dataFrame["Matches"])ExampleFollowing is the code −import seaborn as sb import pandas as pd import matplotlib.pyplot as plt # Load data from a CSV file into a ... Read More
Violin Plot in Seaborn is used to draw a combination of boxplot and kernel density estimate. The seaborn.violinplot() is used for this. Observations show as a stick using the inner parameter with value stick.Let’s say the following is our dataset in the form of a CSV file − Cricketers.csvAt first, import the required libraries −import seaborn as sb import pandas as pd import matplotlib.pyplot as pltLoad data from a CSV file into a Pandas DataFrame −dataFrame = pd.read_csv("C:\Users\amit_\Desktop\Cricketers.csv") Plotting violin plot with Academy and Age. Control order by passing an explicit order i.e. ordering on the basis of "Academy". Observations ... Read More
Let’s say the following is our CSV file −SalesRecords.csvAnd we need to generate 3 excel files from the above existing CSV file. The 3 CSV files should be on the basis of the Car names i.e. BMW.csv, Lexus.csv and Jaguar.csv.At first, read our input CSV file i.e. SalesRecord.csv −dataFrame = pd.read_csv("C:\Users\amit_\Desktop\SalesRecords.csv")Use groupby() to generate CSVs on the basis of Car names in Car column −for (car), group in dataFrame.groupby(['Car']): group.to_csv(f'{car}.csv', index=False)ExampleFollowing is the code −import pandas as pd # DataFrame to read our input CS file dataFrame = pd.read_csv("C:\Users\amit_\Desktop\SalesRecords.csv") print("Input CSV file = ", dataFrame) ... Read More
To write pandas dataframe to a CSV file in Python, use the to_csv() method. At first, let us create a dictionary of lists −# dictionary of lists d = {'Car': ['BMW', 'Lexus', 'Audi', 'Mercedes', 'Jaguar', 'Bentley'], 'Date_of_purchase': ['2020-10-10', '2020-10-12', '2020-10-17', '2020-10-16', '2020-10-19', '2020-10-22'] }Now, create pandas dataframe from the above dictionary of lists −dataFrame = pd.DataFrame(d) Our output CSV file will generate on the Desktop since we have set the Desktop path below −dataFrame.to_csv("C:\Users\amit_\Desktop\sales1.csv\SalesRecords.csv")ExampleFollowing is the code −import pandas as pd # dictionary of lists d = {'Car': ['BMW', 'Lexus', 'Audi', 'Mercedes', 'Jaguar', 'Bentley'], 'Date_of_purchase': ['2020-10-10', '2020-10-12', '2020-10-17', '2020-10-16', ... Read More
Suppose we have an array containing various integer values and a given length k. We have to find out the greatest subarray from the array of the given length. A subarray is said to be greater than another subarray, if subarray1[i] ≠ subarry2[i] and subarray1[i] > subarry2[i].So, if the input is like nums = [5, 3, 7, 9], k = 2, then the output will be [7, 9].To solve this, we will follow these steps −start := size of nums - kmax_element := nums[start]max_index := startwhile start >= 0, doif nums[start] > max_element is non-zero, thenmax_element := nums[start]max_index := startreturn ... Read More
Violin Plot in Seaborn is used to draw a combination of boxplot and kernel density estimate. The seaborn.violinplot() is used for this. Plot a sinle violinplot usinga single column.Let’s say the following is our dataset in the form of a CSV file − Cricketers.csvAt first, import the required libraries −import seaborn as sb import pandas as pd import matplotlib.pyplot as pltLoad data from a CSV file into a Pandas DataFrame −dataFrame = pd.read_csv("C:\Users\amit_\Desktop\Cricketers.csv") Plotting single horizontal violin plot with Weight (kgs) column −sb.violinplot(dataFrame['Weight'])ExampleFollowing is the code −import seaborn as sb import pandas as pd import matplotlib.pyplot as plt # ... Read More
Count Plot in Seaborn is used to display the counts of observations in each categorical bin using bars. The seaborn.countplot() is used for this. Style the bars using the facecolor, linewidth and edgecolor parameters.Let’s say the following is our dataset in the form of a CSV file − Cricketers.csvAt first, import the required libraries −import seaborn as sb import pandas as pd import matplotlib.pyplot as pltLoad data from a CSV file into a Pandas DataFrame −dataFrame = pd.read_csv("C:\Users\amit_\Desktop\Cricketers.csv") Style and design the bars using the facecolor, linewidth and edgecolor parameters −sb.countplot(dataFrame["Age"], facecolor=(0, 0.0, 0, 0), linewidth=3, edgecolor=sb.color_palette("dark", 2))ExampleFollowing is the ... Read More
Point Plot in Seaborn is used to show point estimates and confidence intervals using scatter plot glyphs. The seaborn.pointplot() is used for this. Set caps to the error bars using the capsize parameter.Let’s say the following is our dataset in the form of a CSV file − Cricketers.csvAt first, import the required libraries −import seaborn as sb import pandas as pd import matplotlib.pyplot as pltLoad data from a CSV file into a Pandas DataFrame −dataFrame = pd.read_csv("C:\Users\amit_\Desktop\Cricketers.csv") Setting caps to the error bars using the capsize parameter −sb.pointplot(dataFrame['Role'], dataFrame['Age'], capsize=.3)ExampleFollowing is the code −import seaborn as sb import pandas as ... Read More
Box Plot in Seaborn is used to draw a box plot to show distributions with respect to categories. The seaborn.boxplot() is used for this. To control the order use the order parameter.Let’s say the following is our dataset in the form of a CSV file − Cricketers.csvAt first, import the required libraries −import seaborn as sb import pandas as pd import matplotlib.pyplot as pltLoad data from a CSV file into a Pandas DataFrame −dataFrame = pd.read_csv("C:\Users\amit_\Desktop\Cricketers.csv") Plotting box plot with Academy and Age. Control box order by passing an explicit order i.e. ordering on the basis of "Academy". Ordering using ... Read More