import pandas as pd

Use .apply to send a column of every row to a function

You can use .apply to send a single column to a function. This is useful when cleaning up data - converting formats, altering values etc.

# What's our data look like?
df = pd.read_csv("../Civil_List_2014.csv").head(3)
df
DPT NAME ADDRESS TTL # PC SAL-RATE
0 868 B J SANDIFORD DEPARTMENT OF CITYWIDE ADM 12702 X $5.00
1 868 C A WIGFALL DEPARTMENT OF CITYWIDE ADM 12702 X $5.00
2 69 A E A-AWOSOGBA HRA/DEPARTMENT OF SOCIAL S 52311 A $51955.00 
# Get rid of $ and , in the SAL-RATE, then convert it to a float
def money_to_float(money_str):
    return float(money_str.replace("$","").replace(",",""))

df['SAL-RATE'].apply(money_to_float)
0        5.0
1        5.0
2    51955.0
Name: SAL-RATE, dtype: float64

# Save the result in a new column
df['salary'] = df['SAL-RATE'].apply(money_to_float)
# Take a peek
df
DPT NAME ADDRESS TTL # PC SAL-RATE salary
0 868 B J SANDIFORD DEPARTMENT OF CITYWIDE ADM 12702 X $5.00 5.0
1 868 C A WIGFALL DEPARTMENT OF CITYWIDE ADM 12702 X $5.00 5.0
2 69 A E A-AWOSOGBA HRA/DEPARTMENT OF SOCIAL S 52311 A $51955.00 51955.0

Use .apply with axis=1 to send every single row to a function

You can also send an entire row at a time instead of just a single column. Use this if you need to use multiple columns to get a result.

# Create a dataframe from a list of dictionaries
rectangles = [
    { 'height': 40, 'width': 10 },
    { 'height': 20, 'width': 9 },
    { 'height': 3.4, 'width': 4 }
]

rectangles_df = pd.DataFrame(rectangles)
rectangles_df
height width
0 40.0 10
1 20.0 9
2 3.4 4 
# Use the height and width to calculate the area
def calculate_area(row):
    return row['height'] * row['width']

rectangles_df.apply(calculate_area, axis=1)
0    400.0
1    180.0
2     13.6
dtype: float64

# Use .apply to save the new column if we'd like
rectangles_df['area'] = rectangles_df.apply(calculate_area, axis=1)
rectangles_df
height width area
0 40.0 10 400.0
1 20.0 9 180.0
2 3.4 4 13.6