Course Content
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. Thefigsize
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 DataFramedata
;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.
Task
- Import
matplotlib.pyplot
andseaborn
asplt
andsns
, respectively. - Plot the
"sentiment"
field from thedata
DataFrame.
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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. Thefigsize
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 DataFramedata
;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.
Task
- Import
matplotlib.pyplot
andseaborn
asplt
andsns
, respectively. - Plot the
"sentiment"
field from thedata
DataFrame.