Pandas DataFrame Histogram Plot
Table Of Contents:
- Syntax ‘plot.hist( )’ Method In Pandas.
- Examples ‘plot.hist( )’ Method.
(1) Syntax:
DataFrame.plot.hist(by=None, bins=10, **kwargs)
Description:
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:
- by: str or sequence, optional – Column in the DataFrame to group by.
- bins: int, 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.
(2) Examples Of plot.hist() Method:
Example-1: 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)
df
Output:
ax = df.plot.hist(bins=12, alpha=0.5)
Output:
# 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})
df
Output:
ax = df.plot.hist(column=["age"], by="gender", figsize=(10, 8))