Pandas Itterows () method ()

The Python Pandas function DataFrame.iterrows() is used to iterate on lines of a dataframe pandas. For each line, it returns a tuple python containing the index as well as a series representing the data of the corresponding line.

How is the syntax of the method iterrows() of pandas?

Pandas base syntax DataFrame.iterrows() is simple, because the function does not take No parameter ::

In the example of code above, df designates the dataframe on which iteration must be carried out.

How to apply the Pandas function iterrows() ?

The function DataFrame.iterrows() is typically used each time we owe Processing line data by line. It is therefore often combined with the loop for in python.

The sum of the values ​​of a column

In what follows, we consider a dataframe with the columns « name », « age » and « points »:

import pandas as pd
# Créer un exemple de DataFrame
data = {'Nom' : ['Anna', 'Ben', 'Clara'],
    'Âge' : [23, 35, 29],
    'Points' : [88, 92, 85]}
df = pd.DataFrame(data)
print(df)

The above code results in the following dataframe:

Nom  Âge  Points
0   Anna   23     88
1    Ben   35     92
2  Clara   29     85

We must now calculate the sum of the points. For this, we can use DataFrame.iterrows() of pandas:

# Calculer la somme des points
total_score = 0
for index, row in df.iterrows():
    total_score += row['Points']
print(f"La somme totale des points est : {total_score}")

In this example, the Pandas function iterrows() is used to iterate on the lines and successively add the values ​​of the « Points » column. The result is thus:

La somme totale des points est : 265

Conditional edition of lines

The function iterrows() Can also be used to apply conditions to certain lines of your dataaframa. For example, suppose you want to extract the names of all people over 30 years old in an existing dataframa:

# Récupérer le nom des personnes de plus de 30 ans
names = []
for index, row in df.iterrows():
    if row['Âge'] > 30:
        names.append(row['Nom'])
print(f"Personnes de plus de 30 ans : {names}")

In the example of code, the dataframa lines are covered using the function DataFrame.iterrows() of pandas. In the loop forthe values ​​of the “age” column are examined in order to store only the names of people over 30 years old in the Python list names. For this, we use the Python function append(). This operation gives the following result:

Personnes de plus de 30 ans : ['Ben']