Python | Pandas DataFrame.blocks Last Updated : 20 Feb, 2019 Summarize Comments Improve Suggest changes Share 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.blocks attribute is synonym for as_blocks() function. It basically convert the frame to a dict of dtype -> Constructor Types that each has a homogeneous dtype. Syntax: DataFrame.blocks Parameter : None Returns : dict Example #1: Use DataFrame.blocks attribute to return a dictionary containing the data in blocks of separate data types. 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]}) # Create the index index_ = ['Row_1', 'Row_2', 'Row_3', 'Row_4', 'Row_5'] # Set the index df.index = index_ # Print the DataFrame print(df) Output : Now we will use DataFrame.blocks attribute to return the block representation of the given dataframe. Python3 1== # return a dictionary result = df.blocks # Print the result print(result) Output : As we can see in the output, the DataFrame.blocks attribute has successfully returned a dictionary containing the data of the dataframe. Homogeneous columns are places in the same block. Example #2: Use DataFrame.blocks attribute to return a dictionary containing the data in blocks of separate data types. 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]}) # Create the index index_ = ['Row_1', 'Row_2', 'Row_3', 'Row_4', 'Row_5'] # Set the index df.index = index_ # Print the DataFrame print(df) Output : Now we will use DataFrame.blocks attribute to return the block representation of the given dataframe. Python3 1== # return a dictionary result = df.blocks # Print the result print(result) Output : As we can see in the output, the DataFrame.blocks attribute has successfully returned a dictionary containing the data of the dataframe. Homogeneous columns are places in the same block. Comment More infoAdvertise with us Next Article Dataframe Attributes in Python Pandas S Shubham__Ranjan Follow Improve Article Tags : Pandas Python-pandas Pandas-DataFrame-Methods AI-ML-DS With Python Similar Reads Python | Pandas DataFrame.ix[ ] Python's Pandas library is a powerful tool for data analysis, it provides DataFrame.ix[] method to select a subset of data using both label-based and integer-based indexing.Important Note: DataFrame.ix[] method has been deprecated since Pandas version 0.20.0 and is no longer recommended for use in n 2 min read Python | Pandas dataframe.eq() 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.eq() is a wrapper used for the flexible comparison. It provides a con 3 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 Python | Pandas dataframe.mask() 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.mask() function return an object of same shape as self and whose corr 3 min read Dataframe Attributes in Python Pandas In this article, we will discuss the different attributes of a dataframe. Attributes are the properties of a DataFrame that can be used to fetch data or any information related to a particular dataframe. The syntax of writing an attribute is: DataFrame_name.attribute These are the attributes of the 11 min read Python | Pandas DataFrame.empty 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 Like