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# How to Create an Ogive Graph in Python

AnÂ ogiveÂ is a graph that shows how many data values lie above or below a certain value in a dataset. This tutorial explains how to create an ogive in Python.

### Example: How to Create an Ogive in Python

Perform the following steps to create an ogive for a dataset in Python.

Step 1: Create a dataset.

First, we can create a simple dataset.

```import numpy as np

#create array of 1,000 random integers between 0 and 10
np.random.seed(1)
data = np.random.randint(0, 10, 1000)

#view first ten values
data[:10]

array([5, 8, 9, 5, 0, 0, 1, 7, 6, 9])
```

Step 2: Create an ogive.

Next, we can use the numpy.histogram function to automatically find the classes and the class frequencies. Then we can use matplotlib to actually create the ogive:

```import numpy as np
import matplotlib.pyplot as plt

#obtain histogram values with 10 bins
values, base = np.histogram(data, bins=10)

#find the cumulative sums
cumulative = np.cumsum(values)

# plot the ogive
plt.plot(base[:-1], cumulative, 'ro-')```

The ogive chart will look different based on the number of bins that we specify in theÂ numpy.histogram function. For example, hereâ€™s what the chart would look like if we used 30 bins:

```#obtain histogram values with 30 bins
values, base = np.histogram(data, bins=10)

#find the cumulative sums
cumulative = np.cumsum(values)

# plot the ogive
plt.plot(base[:-1], cumulative, 'ro-')```

The argument â€˜ro-â€˜Â specifies:

• Use the color red (r)
• Use circles at each class break (o)
• Use lines to connect the circles (-)

Feel free to change these options to change the aesthetics of the chart.