Coding Ref

In Pandas, the `min`

method is used to return the minimum value in a DataFrame. This method will return the minimum value in each column of the DataFrame, unless a specific column is specified.

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 find the minimum value in each column of this DataFrame, you could use the following code:

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]
})
# Find the minimum value in each column
min_values = df.min()
# Print the minimum values
print(min_values)
```

output

```
A 1
B 10
C 100
dtype: int64
```

In the code above, the `min`

method is applied to the DataFrame, without specifying a specific column.

This returns a `Series`

object containing the minimum value in each column. In this case, the minimum values are 1, 10, and 100 for columns `A`

, `B`

, and `C`

, respectively.

You can also use the `min`

method to find the minimum value in a specific column of the DataFrame.

For example, to find the minimum value in column `B`

, 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]
})
# Find the minimum value in column B
min_value = df['B'].min()
# Print the minimum value
print(min_value)
```

In the code above, the `min`

method is applied to the `B`

column of the DataFrame. This returns the minimum value in that column, which is `10`

in this case.

You can also use the `min`

method to find the minimum value in multiple columns of the DataFrame.

For example, if you wanted to find the minimum value in either column `B`

or column `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]
})
# Find the minimum value in columns B and C
min_value = df[['A', 'B']].min().min()
# Print the minimum value
print(min_value)
```

In the code above, the `min`

method is applied to the `A`

and `B`

columns of the DataFrame.

This returns the minimum value in either of these two columns, which is `1`

in this case.

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