Coding Ref

To get the absolute value for a column in Pandas, you can use the `abs`

method.

This method is applied to a `Series`

object and returns a new `Series`

object containing the absolute values for each element in the original `Series`

.

For example, consider the following DataFrame:

main.py

```
import pandas as pd
df = pd.DataFrame({
'A': [1, -2, 3, -4, 5],
'B': [10, -20, 30, -40, 50],
'C': [100, -200, 300, -400, 500]
})
```

This DataFrame has three columns `A`

, `B`

, and `C`

, with five rows of data. To get the absolute values for a specific column, you could do the following:

main.py

```
import pandas as pd
df = pd.DataFrame({
'A': [1, -2, 3, -4, 5],
'B': [10, -20, 30, -40, 50],
'C': [100, -200, 300, -400, 500]
})
# Get the absolute values for column B
abs_values = df['B'].abs()
# Print the resulting Series
print(abs_values)
```

In the code above, the `abs`

method is applied to the `B`

column of the DataFrame, which returns a new `Series`

object containing the absolute values for the `B`

column. In this case, the resulting `Series`

has five elements with the absolute values 10, 20, 30, 40, and 50.

You can also specify multiple columns when using the `abs`

method. For example, if you wanted to get the absolute values for both columns `B`

and `C`

, you could do the following:

main.py

```
import pandas as pd
df = pd.DataFrame({
'A': [1, -2, 3, -4, 5],
'B': [10, -20, 30, -40, 50],
'C': [100, -200, 300, -400, 500]
})
# Get the absolute values for columns B and C
abs_values = df[['B', 'C']].abs()
# Print the resulting DataFrame
print(abs_values)
```

In the code above, the `abs`

method is applied to the `B`

and `C`

columns of the DataFrame, which returns a new `DataFrame`

object containing the absolute values for these two columns.

In this case, the resulting `DataFrame`

has five rows and two columns (`B`

and `C`

), with the absolute values for each element in the original `DataFrame`

.

You can also use the `abs`

method to get the absolute values for the entire DataFrame. This method will return a new DataFrame with the absolute value of each element in the original DataFrame.

To do this, you can use the `apply`

method in combination with the `abs`

method, as shown in the following example:

main.py

```
import pandas as pd
# create a sample DataFrame
df = pd.DataFrame({'A': [-5, 3, 2, -1], 'B': [6, -2, 0, 8], 'C': [-3, 4, 1, -7]})
# calculate the absolute value of each element in the DataFrame
abs_df = df.abs()
# print the resulting DataFrame
print(abs_df)
```

This code will output the following DataFrame:

output

```
A B C
0 5 6 3
1 3 2 4
2 2 0 1
3 1 8 7
```

As you can see, the `abs()`

method was applied to each element in the original DataFrame, and the resulting DataFrame contains the absolute value of each element.

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