Notice: This page requires JavaScript to function properly.
Please enable JavaScript in your browser settings or update your browser.
Plot the Distribution | Tweet Sentiment Analysis
Tweet Sentiment Analysis
course content

Conteúdo do Curso

Tweet Sentiment Analysis

Plot the Distribution

Plotting the distribution of a variable refers to creating a visual representation of the distribution of values for that variable. Several types of plots can be used to display the distribution of a variable, each with its strengths and weaknesses.

For this chapater, we will use histograms. A histogram is a plot that shows the frequency of different values in a dataset. It is a useful way to visualize the distribution of a continuous variable. The x-axis represents the variable of interest and the y-axis represents the frequency.

Methods description

  • matplotlib.pyplot: This module provides a MATLAB-like plotting framework. In this code, it's used to create and customize the plot;
  • seaborn: Seaborn is a Python visualization library based on matplotlib. It provides a high-level interface for drawing attractive and informative statistical graphics. Here, it's used to create the count plot;
  • plt.figure(figsize=(12, 6)): This method creates a new figure with a specified size. The figsize parameter sets the width and height of the figure in inches;
  • sns.countplot(x="sentiment", data=data): This method from seaborn generates a count plot. It plots the count of observations in each category of the specified categorical variable ("sentiment" in this case) using data from the provided DataFrame data;
  • plt.show(): This method displays the plot. It's typically used when creating plots in non-interactive environments (like scripts or Jupyter notebooks) to show the generated plot.

Tarefa

  1. Import matplotlib.pyplot and seaborn as plt and sns, respectively.
  2. Plot the "sentiment" field from the data DataFrame.

Tarefa

  1. Import matplotlib.pyplot and seaborn as plt and sns, respectively.
  2. Plot the "sentiment" field from the data DataFrame.

Mark tasks as Completed
Mude para o desktop para praticar no mundo realContinue de onde você está usando uma das opções abaixo

Tudo estava claro?

Plotting the distribution of a variable refers to creating a visual representation of the distribution of values for that variable. Several types of plots can be used to display the distribution of a variable, each with its strengths and weaknesses.

For this chapater, we will use histograms. A histogram is a plot that shows the frequency of different values in a dataset. It is a useful way to visualize the distribution of a continuous variable. The x-axis represents the variable of interest and the y-axis represents the frequency.

Methods description

  • matplotlib.pyplot: This module provides a MATLAB-like plotting framework. In this code, it's used to create and customize the plot;
  • seaborn: Seaborn is a Python visualization library based on matplotlib. It provides a high-level interface for drawing attractive and informative statistical graphics. Here, it's used to create the count plot;
  • plt.figure(figsize=(12, 6)): This method creates a new figure with a specified size. The figsize parameter sets the width and height of the figure in inches;
  • sns.countplot(x="sentiment", data=data): This method from seaborn generates a count plot. It plots the count of observations in each category of the specified categorical variable ("sentiment" in this case) using data from the provided DataFrame data;
  • plt.show(): This method displays the plot. It's typically used when creating plots in non-interactive environments (like scripts or Jupyter notebooks) to show the generated plot.

Tarefa

  1. Import matplotlib.pyplot and seaborn as plt and sns, respectively.
  2. Plot the "sentiment" field from the data DataFrame.

Mark tasks as Completed
Mude para o desktop para praticar no mundo realContinue de onde você está usando uma das opções abaixo
Seção 1. Capítulo 6
AVAILABLE TO ULTIMATE ONLY
We're sorry to hear that something went wrong. What happened?
some-alt