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To add a new row to a pandas dataframe based on certain conditions and update existing rows, the following steps can be taken:

1. Create a new row as a dictionary with the desired values for each column.

new_row = {'column_1': value_1, 'column_2': value_2, ...}

1. Determine the conditions under which the row should be added or updated. For example, if the row should be added if the value in column_1 is greater than a certain threshold:

if value_1 > threshold:
    # add or update row

1. Use the df.loc[ ] method to add or update the row. If the condition is met, the new row can be added using the append() method. If an existing row should be updated, the loc[ ] method can be used to find the row and update the desired columns.

if value_1 > threshold:
    new_df = df.append(new_row, ignore_index=True)
    # or
    df.loc[index, 'column_1'] = new_value

1. Save the changes to the dataframe using the to_csv() method.

df.to_csv('filename.csv', index=False)