Python | Pandas dataframe.std() Last Updated : 22 Oct, 2019 Summarize Comments Improve Suggest changes Share Like Article Like Report 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.std() function return sample standard deviation over requested axis. By default the standard deviations are normalized by N-1. It is a measure that is used to quantify the amount of variation or dispersion of a set of data values. For more information click here Syntax : DataFrame.std(axis=None, skipna=None, level=None, ddof=1, numeric_only=None, **kwargs) Parameters : axis : {index (0), columns (1)} skipna : Exclude NA/null values. If an entire row/column is NA, the result will be NA level : If the axis is a MultiIndex (hierarchical), count along a particular level, collapsing into a Series ddof : Delta Degrees of Freedom. The divisor used in calculations is N - ddof, where N represents the number of elements. numeric_only : Include only float, int, boolean columns. If None, will attempt to use everything, then use only numeric data. Not implemented for Series. Return : std : Series or DataFrame (if level specified) For link to the CSV file used in the code, click here Example #1: Use std() function to find the standard deviation of data along the index axis. Python3 # importing pandas as pd import pandas as pd # Creating the dataframe df = pd.read_csv("nba.csv") # Print the dataframe df Now find the standard deviation of all the numeric columns in the dataframe. We are going to skip the NaN values in the calculation of the standard deviation. Python3 1== # finding STD df.std(axis = 0, skipna = True) Output : Example #2: Use std() function to find the standard deviation over the column axis. Find the standard deviation along the column axis. We are going to set skipna to be true. If we do not skip the NaN values then it will result in NaN values. Python3 # importing pandas as pd import pandas as pd # Creating the dataframe df = pd.read_csv("nba.csv") # STD over the column axis. df.std(axis = 1, skipna = True) Output : Comment More infoAdvertise with us Next Article Pandas DataFrame.astype()-Python S Shubham__Ranjan Follow Improve Article Tags : Technical Scripter Python Python-pandas Python pandas-dataFrame Pandas-DataFrame-Methods +1 More Practice Tags : python Similar Reads Python | Pandas DataFrame.values 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 Pandas DataFrame.to_string-Python Pandas is a powerful Python library for data manipulation, with DataFrame as its key two-dimensional, labeled data structure. It allows easy formatting and readable display of data. DataFrame.to_string() function in Pandas is specifically designed to render a DataFrame into a console-friendly tabula 5 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.transform 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 3 min read Pandas DataFrame.astype()-Python DataFrame.astype() function in pandas cast a pandas object such as a DataFrame or Series to a specified data type. This is especially useful when you need to ensure that columns have the correct type, such as converting strings to integers or floats to strings. For example:Pythonimport pandas as pd 3 min read Python | Pandas DataFrame.ftypes 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