How to apply arithmatic operations on a Pandas DataFrame?
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# How to apply arithmatic operations on a Pandas DataFrame?

This recipe helps you apply arithmatic operations on a Pandas DataFrame

0

## Recipe Objective

Have you ever tried to apply some operation in dataframe on string and numeric data.

So this is the recipe on how we can apply arithmatic operations on a Pandas DataFrame.

## Step 1 - Import the library

``` import pandas as pd import numpy as np ```

We have only imported pandas and numpy which is needed.

## Step 2 - Creating DataFrame

We have created a dictionary and passed it through pd.DataFrame to create a Dataframe ``` raw_data = {"first_name": ["Sheldon", "Raj", "Leonard", "Howard", "Amy"], "age": [42, 38, 36, 41, 35], "Comedy_Score": [9, 7, 8, 8, 5], "Rating_Score": [25, 25, 49, 62, 70]} df = pd.DataFrame(raw_data, columns = ["first_name", "age", "Comedy_Score", "Rating_Score"]) print(df) ```

## Step 3 - Applying Different Operation

We are making each letter of string in first name as capital. For this we creating a lambda function and by which are making every letter capital. ``` capitalizer = lambda x: x.upper() print(df["first_name"].apply(capitalizer)) ``` Now lets say we want to find the square root of the values in the dataframe. For this we have to remove the features which has strings so we have droped the feature first name. Now using applymap we have calculated square root of each values. ``` df = df.drop("first_name", axis=1) print(df) print(df.applymap(np.sqrt)) ``` Now lets say we want to multiply each value by 100. So for this we have created a function times100. In which we have used if else statements to return the same value if it is a string and multiply it by 100 if it is a numeric value. We have applied this function on every value of the dataframe. ``` def times100(x): if type(x) is str: return x elif x: return 100 * x else: return print(df.applymap(times100)) ``` So the output comes as

```  first_name  age  Comedy_Score  Rating_Score
0    Sheldon   42             9            25
1        Raj   38             7            25
2    Leonard   36             8            49
3     Howard   41             8            62
4        Amy   35             5            70

0    SHELDON
1        RAJ
2    LEONARD
3     HOWARD
4        AMY
Name: first_name, dtype: object

0    SHELDON
1        RAJ
2    LEONARD
3     HOWARD
4        AMY
Name: first_name, dtype: object

age  Comedy_Score  Rating_Score
0   42             9            25
1   38             7            25
2   36             8            49
3   41             8            62
4   35             5            70

age  Comedy_Score  Rating_Score
0  6.480741      3.000000      5.000000
1  6.164414      2.645751      5.000000
2  6.000000      2.828427      7.000000
3  6.403124      2.828427      7.874008
4  5.916080      2.236068      8.366600

age  Comedy_Score  Rating_Score
0  4200           900          2500
1  3800           700          2500
2  3600           800          4900
3  4100           800          6200
4  3500           500          7000
​
```

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