Pandy usuwają wiersz, jeśli brakuje wartości w kolumnie
# remove all rows without a value in the 'name' column
df = df[df['name'].notna()]
Trained Tuna
# remove all rows without a value in the 'name' column
df = df[df['name'].notna()] df.dropna() #drop all rows that have any NaN values
df.dropna(how='all')# Drop rows which contain any NaN value in the selected columns
mod_df = df.dropna( how='any',
subset=['Name', 'Age'])