# Iterating over a DataFrame

### Create a sample dataframe

    # Import modules
    import pandas as pd

    # Example dataframe

    raw_data  = {'fruit': ['Banana', 'Orange', 'Apple', 'lemon', "lime", "plum"],
            'color': ['yellow', 'orange', 'red', 'yellow', "green", "purple"],
            'kcal': [89, 47, 52, 15, 30, 28]
        }

    df = pd.DataFrame(raw_data, columns = ['fruit', 'color', 'kcal'])
    df

| fruit | color | kcal
--- | --- | --- | ---
0 | Banana | yellow | 89
1 | Orange | orange | 47
2 | Apple | red | 52
3 | lemon | yellow | 15
4 | lime | green | 30
5 | plum | purple | 28

### Using the iterrows method

Pandas DataFrames can return a generator with the iterrrows method. It can then be used to loop over the rows of the DataFrame

    for index, row in df.iterrows():
        print("At line {0} there is a {1} which is {2} and contains {3} kcal".format(index, row["fruit"], row["color"], row["kcal"]))

    At line 0 there is a Banana which is yellow and contains 89 kcal
    At line 1 there is a Orange which is orange and contains 47 kcal
    At line 2 there is a Apple which is red and contains 52 kcal
    At line 3 there is a lemon which is yellow and contains 15 kcal
    At line 4 there is a lime which is green and contains 30 kcal
    At line 5 there is a plum which is purple and contains 28 kcal

### Find an error or bug? Have a suggestion?

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