Often, it is essential to find and replace some values inside a dataframe. This can be done with the following steps:

1. We can use the replace method in such cases:

import numpy as np
replaceFrame = pd.DataFrame({'column 1': [200., 3000., -786., 3000., 234., 444., -786., 332., 3332. ], 'column 2': range(9)})
replaceFrame.replace(to_replace =-786, value= np.nan)

The output of the preceding code is as follows:

Note that we just replaced one value with the other values. We can also replace multiple values at once.

2. In order to do so, we display them using a list:

replaceFrame = pd.DataFrame({'column 1': [200., 3000., -786., 3000., 234., 444., -786., 332., 3332. ], 'column 2': range(9)})
replaceFrame.replace(to_replace =[-786, 0], value= [np.nan, 2])

In the preceding code, there are two replacements. All -786 values will be replaced by NaN and all 0 values will be replaced by 2. That's pretty straightforward, right?