Python | Pandas DataFrame.values Last Updated : 20 Feb, 2019 Comments Improve Suggest changes Like Article Like Report Pandas DataFrame is a two-dimensional size-mutable, potentially heterogeneous tabular data structure with labeled axes (rows and columns). Arithmetic operations align on both row and column labels. It can be thought of as a dict-like container for Series objects. This is the primary data structure of the Pandas. Pandas DataFrame.values attribute return a Numpy representation of the given DataFrame. Syntax: DataFrame.values Parameter : None Returns : array Example #1: Use DataFrame.values attribute to return the numpy representation of the given DataFrame. Python3 # importing pandas as pd import pandas as pd # Creating the DataFrame df = pd.DataFrame({'Weight':[45, 88, 56, 15, 71], 'Name':['Sam', 'Andrea', 'Alex', 'Robin', 'Kia'], 'Age':[14, 25, 55, 8, 21]}) # Print the DataFrame print(df) Output : Now we will use DataFrame.values attribute to return the numpy representation of the given DataFrame. Python3 1== # return the numpy representation of # this dataframe result = df.values # Print the result print(result) Output : As we can see in the output, the DataFrame.values attribute has successfully returned the numpy representation of the given DataFrame. Example #2: Use DataFrame.values attribute to return the numpy representation of the given DataFrame. Python3 # importing pandas as pd import pandas as pd # Creating the 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 the DataFrame print(df) Output : Now we will use DataFrame.values attribute to return the numpy representation of the given DataFrame. Python3 1== # return the numpy representation of # this dataframe result = df.values # Print the result print(result) Output : As we can see in the output, the DataFrame.values attribute has successfully returned the numpy representation of the given DataFrame. Comment More infoAdvertise with us Next Article Python | Pandas DataFrame.values S Shubham__Ranjan Follow Improve Article Tags : Python Python-pandas Python pandas-dataFrame Pandas-DataFrame-Methods Practice Tags : python Similar Reads Python | Pandas dataframe.set_value() Python is a great language for doing data analysis, primarily because of the fantastic ecosystem of data-centric python packages. Pandas is one of those packages and makes importing and analyzing data much easier. Pandas dataframe.set_value() function put a single value at passed column and index. I 2 min read Python | Pandas Index.values Pandas Index is an immutable ndarray implementing an ordered, sliceable set. It is the basic object which stores the axis labels for all pandas objects. Pandas Index.values attribute return an array representing the data in the given Index object. Syntax: Index.values Parameter : None Returns : an a 2 min read Python | Pandas Dataframe.at[ ] Python is a great language for doing data analysis, primarily because of the fantastic ecosystem of data-centric Python packages. Pandas is one of those packages and makes importing and analyzing data much easier. Pandas at[] is used to return data in a dataframe at the passed location. The passed l 2 min read Python | Pandas DataFrame.to_records Pandas DataFrame is a two-dimensional size-mutable, potentially heterogeneous tabular data structure with labeled axes (rows and columns). Arithmetic operations align on both row and column labels. It can be thought of as a dict-like container for Series objects. This is the primary data structure o 2 min read Python | Pandas Dataframe.iat[ ] Python is a great language for doing data analysis, primarily because of the fantastic ecosystem of data-centric Python packages. Pandas is one of those packages and makes importing and analyzing data much easier. Pandas iat[] method is used to return data in a dataframe at the passed location. The 2 min read Like