pandas.Series.plot.hist#
- Series.plot.hist(by=None, bins=10, **kwargs)[source]#
Draw one histogram of the DataFrame’s columns.
A histogram is a representation of the distribution of data. This function groups the values of all given Series in the DataFrame into bins and draws all bins in one
matplotlib.axes.Axes
. This is useful when the DataFrame’s Series are in a similar scale.- Parameters
- bystr or sequence, optional
Column in the DataFrame to group by.
Changed in version 1.4.0: Previously, by is silently ignore and makes no groupings
- binsint, default 10
Number of histogram bins to be used.
- **kwargs
Additional keyword arguments are documented in
DataFrame.plot()
.
- Returns
- class:matplotlib.AxesSubplot
Return a histogram plot.
See also
DataFrame.hist
Draw histograms per DataFrame’s Series.
Series.hist
Draw a histogram with Series’ data.
Examples
When we roll a die 6000 times, we expect to get each value around 1000 times. But when we roll two dice and sum the result, the distribution is going to be quite different. A histogram illustrates those distributions.
>>> df = pd.DataFrame( ... np.random.randint(1, 7, 6000), ... columns = ['one']) >>> df['two'] = df['one'] + np.random.randint(1, 7, 6000) >>> ax = df.plot.hist(bins=12, alpha=0.5)
A grouped histogram can be generated by providing the parameter by (which can be a column name, or a list of column names):
>>> age_list = [8, 10, 12, 14, 72, 74, 76, 78, 20, 25, 30, 35, 60, 85] >>> df = pd.DataFrame({"gender": list("MMMMMMMMFFFFFF"), "age": age_list}) >>> ax = df.plot.hist(column=["age"], by="gender", figsize=(10, 8))