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Python | Pandas DataFrame.values

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.

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