DataFrame.values Pandas DataFrame.values returns a Numpy representation of the given DataFrame.

Syntax: DataFrame.values ​​

Parameter: None

Returns: array

Example # 1: Use the DataFrame.values ​​ attribute to return an empty representation of the given DataFrame.

# import pandas as pd import pandas as pd   # Create DataFrame df = pd.DataFrame ({ `Weight` : [ 45 < code class = "plain">, 88 , 56 , 15 , 71 ], `Name` : [ `Sam` , ` Andrea` , `Alex` , `Robin` , ` Kia` ], `Age` : [ 14 , 25 , 55 , 8 , 21 ]})   # Print DataFrame print (df)

Output:

Now we will use the DataFrame.values ​​attribute to return an empty view of the given DataFrame.

# return empty view # this data frame result = df. values ​​   # Print result   print (result)

Output:

As we can see in the output, the DataFrame.values ​​ attribute has successfully returned an empty representation of the given DataFrame.

Example # 2: Use the attribute DataFrame.values ​​ to return an empty view of the given DataFrame.

# import pandas as pd import pandas as pd   # Create DataFrame df = pd.DataFrame ({ "A" : [ 12 , 4 , 5 , None , 1 ],  "B" : [ 7 , 2 , 54 , 3 , None ],  "C" : [ 20 , 16 , 11 , 3  , 8 ],  "D" : [ 14 , 3 , None , 2 , 6 ]})    # Print DataFrame print (df)

Output:

We will now use the DataFrame.values ​​ attribute to return an empty representation of the given DataFrame.

# return empty view # this data frame result = df.values ​​   # Print result print (result)

Output:

As we can see in the output, the DataFrame.values ​​ attribute has successfully returned an empty representation of the given DataFrame.