Sometimes, we want to dynamically evaluate an expression from a formula in Python Pandas.

In this article, we’ll look at how to dynamically evaluate an expression from a formula in Python Pandas.

### How to dynamically evaluate an expression from a formula in Python Pandas?

To dynamically evaluate an expression from a formula in Python Pandas, we can use `eval`

.

For instance, we write

```
np.random.seed(0)
df1 = pd.DataFrame(np.random.choice(10, (5, 4)), columns=list('ABCD'))
df2 = pd.DataFrame(np.random.choice(10, (5, 4)), columns=list('ABCD'))
df3 = pd.DataFrame(np.random.choice(10, (5, 4)), columns=list('ABCD'))
df4 = pd.DataFrame(np.random.choice(10, (5, 4)), columns=list('ABCD'))
x = 5
pd.eval("df1.A + (df1.B * x)")
```

to create a few datadrames with `DataFrame`

.

Then we call `eval`

with an expression string that gets the values from the dataframes and multiply `df1.B`

by `x`

.

### Conclusion

To dynamically evaluate an expression from a formula in Python Pandas, we can use `eval`

.