To find the product of the values in columns in a DataFrame, or the product of the values of a Series in pandas, the easiest way is to use the pandas **prod()** function.

```
df.prod() # Calculate products for all columns
df["Column"].prod() #calculate product for 1 column
```

The pandas **product()** function is equivalent to the pandas **prod()** function.

You can also use the numpy **prod()** function.

`np.prod(df["Column"]) #calculate sum for 1 column`

When working with data, many times we want to calculate summary statistics to understand our data better. One such statistic is the product, or the multiplicative total of a list of numbers.

Finding the product of a column, or the product for all columns in a DataFrame using pandas is easy. We can use the pandas **prod()** function to find the total of a column of numbers, or a DataFrame.

Let’s say we have the following DataFrame.

```
df = pd.DataFrame({'Age': [43,23,71,49,52,37],
'Test_Score':[90,87,92,96,84,79]})
print(df)
# Output:
Age Test_Score
0 43 90
1 23 87
2 71 92
3 49 96
4 52 84
5 37 79
```

To get the product for all columns, we can call the pandas **prod()** function.

```
print(df.prod())
# Output:
Age 6619966444
Test_Score 458909660160
dtype: int64
```

If we only want to get the product of just one column, we can do this using the pandas **prod()** function in the following Python code:

```
print(df["Test_Score"].prod())
# Output:
458909660160
```

If you want to see how the product is calculated step by step, you can use the pandas cumprod() function and return a Series for each column with the cumulative product at each point.

## Using numpy prod to Calculate a Product in pandas DataFrame

We can also use the numpy **prod()** function to calculate the product of the numbers in a column in a pandas DataFrame.

To get the product of the numbers in the column “Test_Score”, we can use the numpy **prod()** function in the following Python code:

```
print(np.prod(df["Test_Score"]))
# Output:
458909660160
```

As you can see above, this is the same value we received from the pandas **prod()** function.

Hopefully this article has been helpful for you to understand how to find the product of numbers in a Series or DataFrame in pandas.