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Python Pandas DataFrame.plot.hist() function plots a DataFramesingle histogram of a column. A histogram represents data in a graphical form. It can create a bar chart of a range. The higher the bar, the more data falls within the range of this bar.

pandas.DataFrame.plot.hist()grammar

DataFrame.sample(by=None, bins=10, **kwargs)

parameter

Return Value

It returns a plotted histogram and AxesSubplotthe data.

Sample code:DataFrame.plot.hist()

DataFrameLet's start by plotting a histogram using a simple .

import pandas as pd
dataframe = pd.DataFrame({'Value':[100, 200, 300]})
print(dataframe)

Ours DataFramelooks like,

 Value
0  100
1  200
2  300

All the parameters of this function are optional. If we do not pass any parameters while executing this function, then it will produce the following output.

import pandas as pd
from matplotlib import pyplot as plt

dataframe = pd.DataFrame({"Value": [100, 200, 300]})

histogram = dataframe.plot.hist()
print(histogram)
plt.show()

Output:

AxesSubplot(0.125,0.125;0.775x0.755)

Example code: DataFrame.plot.hist()Plotting a complex histogram

Now, we're going to convert our DataFrameto a complex case.

import pandas as pd
import numpy as np

dataframe = pd.DataFrame(np.random.randint(0, 200, size=(200, 3)), columns=list("ABC"))

print(dataframe)

Our DataFramebecomes:

 A    B    C
0     15  163  163
1     29    7   54
2    195   40    6
3    183   92   57
4     72  167   40
..   ...  ...  ...
195   79   35    7
196  122   79  142
197  121   46  124
198  138  141  114
199  148   95  129

[200 rows x 3 columns]

We have created a containing random integers using the NumPy.random.randint() function DataFrame. Now, we will DataFrame.plot.hist()plot DataFramea histogram of this using the function.

import pandas as pd
import numpy as np

from matplotlib import pyplot as plt

dataframe = pd.DataFrame(np.random.randint(0, 200, size=(200, 3)), columns=list("ABC"))

histogram = dataframe.plot.hist()
print(histogram)
plt.show()

Output:

AxesSubplot(0.125,0.125;0.775x0.755)

This function draws a histogram, with 10 by default bin. It shows DataFramethe frequency distribution of the three columns in . Each column is represented by a specific color.

Example code: DataFrame.plot.hist()Changing binthe quantity

import pandas as pd
import numpy as np
from matplotlib import pyplot as plt

dataframe = pd.DataFrame(np.random.randint(0, 200, size=(200, 3)), columns=list("ABC"))

histogram = dataframe.plot.hist(bins=2)
print(histogram)
plt.show()

Output:

AxesSubplot(0.125,0.125;0.775x0.755)

import pandas as pd
import numpy as np
from matplotlib import pyplot as plt

dataframe = pd.DataFrame(np.random.randint(0, 200, size=(200, 3)), columns=list("ABC"))

histogram = dataframe.plot.hist(bins=50)
print(histogram)
plt.show()

Output:

AxesSubplot(0.125,0.125;0.775x0.755)

In the first example code, we binschanged the number to 2, and in the second example code, it was 50. Notice that binsthe more numbers there are, the easier it is to understand the histogram. The first histogram is blurry because we can't see Athe bars.