I have a huge data-frame. How should I replace a range of values (-200, -100) with NaN?

dataframe

You can use pd.DataFrame.mask:

df.mask((df >= -200) & (df <= -100), inplace=True)

This method replaces elements identified by True values in a Boolean array with a specified value, defaulting to NaN if a value is not specified.

Equivalently, use pd.DataFrame.where with the reverse condition:

df.where((df < -200) | (df > -100), inplace=True)

series

As with many methods, Pandas helpfully includes versions which work with series rather than an entire dataframe. So, for a column df['A'], you can use pd.Series.mask with pd.Series.between:

df['A'].mask(df['A'].between(-200, -100), inplace=True)

For chaining, note inplace=False by default, so you can also use:

df['A'] = df['A'].mask(df['A'].between(-200, -100))