Modify Data

To override the data of a specific cell, column, or row, you can assign a new value to it:

df["existing_col"] = new_value            # Mofidy column
df.loc[index] = new_value                 # Modify row
df.loc[index, "existing_col"] = new_value # modify cell

To update the column value of rows that meet a specific condition use the same condition, we learned in previous lessons with the .loc method:

df.loc[df['col'] > 5, 'existing_col'] = new_value
 
df.loc[(df['col'] <= 5) & (df['col'] > 2), 'existing_col'] = new_value

It is important to use the loc keyword when modifying existing rows. Frequently, when modifying a dataframe without loc, you're dealing with a copy rather than the original data. For example:

df[(df['col'] <= 5) & (df['col'] > 2)]["existing_col"] = new_value

Here, the condition returns a copy of the dataframe instead of the original data.