CODEWITHSUNDEEP
pythonpandasmatplotlibplot
Withoutahold
Withoutahold

Reputation: 31

Pass Plot to Function Matplotlib Python

I was hoping to create a function that will set the x axis limit for a plot. Here is what is working currently:

import matplotlib.pyplot as plt

def scatter_plot(df, user_conditions):
    data_to_plot = user_conditions['data_to_plot']
    title = data_to_plot.replace("_", " ").title()
    df1 = df[['time',data_to_plot]]
    df1 = index_dataframe_time(df1)
    plt.scatter(df1.index.to_pydatetime(), df1[data_to_plot])
    min = df1.index.min()
    max = df1.index.max()
    plt.xlim(min, max)
    plt.title('Hour of Day vs '+title, fontsize=14)
    plt.show()

Here is what I was hoping for:

def scatter_plot(df, user_conditions):
    data_to_plot = user_conditions['data_to_plot']
    title = data_to_plot.replace("_", " ").title()
    print title
    df1 = df[['time',data_to_plot]]
    df1 = index_dataframe_time(df1)
    plot = plt.scatter(df1.index.to_pydatetime(), df1[data_to_plot])
    plot = set_limits(df1, plot)
    plot.title('Hour of Day vs '+title, fontsize=14)
    plot.show()

def set_limits(df, plot):
    min = df.index.min()
    max = df.index.max()
    plot.xlim(min, max)
    return plot

However, there is an issue in set_limits with plot.xlim(min,max),

> Traceback (most recent call last):   
File
> "C:/Users/Application/main.py", line 115, in <module>
>     
main()   
> 
> File "C:/Users/Application/main.py", line
> 106,
> in main
>     plot_configuration(df, user_conditions)   File "C:/Users/Application/main.py", line 111,
> in plot_configuration
>     scatter_plot(df, user_conditions)   
File "C:/Users/Application/main.py", line 76,
> in scatter_plot
>     plot = set_limits(df1, plot)   File "C:/Users/Application/main.py", line 83,
> in set_limits
>     plot.xlim(min, max) AttributeError: 'PathCollection' object has no attribute 'xlim'

How can set_limits be modified in order to fix this?

Upvotes: 1

Views: 6693

Answers (1)

tacaswell
tacaswell

Reputation: 87376

You probably want to be doing something like this:

import matplotlib.pyplot as plt

def scatter_plot(ax, df, user_conditions):
    """
    Parameters
    ----------
    ax : matplotlib.axes.Axes
        The axes to put the data on
    df : pd.DataFrame
        The data
    user_conditions : dict (?)
        bucket of user input to control plotting?
    """
    data_to_plot = user_conditions['data_to_plot']
    title = data_to_plot.replace("_", " ").title()
    print(title)
    df1 = df[['time',data_to_plot]]
    df1 = index_dataframe_time(df1)
    # sc = ax.scatter(df1.index.to_pydatetime(), df1[data_to_plot])
    # only works in 1.5.0+
    sc = ax.scatter(df1.index.to_pydatetime(), data_to_plot,
                    data=df)
    set_limits(df1, ax)
    ax.set_title('Hour of Day vs '+title, fontsize=14)

    return sc

def set_limits(df, ax):
    min = df.index.min()
    max = df.index.max()
    ax.set_xlim(min, max)


fig, ax = plt.subplots()
arts = scatter_plot(ax, df, user_conditions)

if you are not varying the size or color of the markers you are better off using ax.plot(..., linestile='none', marker='o') which will render faster. In this case something like (if you have 1.5.0+)

ax.plot(data_to_plot, linestyle='none', marker='o', data=df)

and it should 'do the right thing'.

Upvotes: 3

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