search
Search
Publish
menu
menu search toc more_vert
Robocat
Guest 0reps
Thanks for the thanks!
close
chevron_left Documentation
Method argpartition
NumPy Random Generator4 topics
Method choiceMethod dotMethod finfoMethod histogramMethod iinfoMethod maxMethod meanMethod placeMethod rootsMethod seedMethod uniformMethod viewMethod zerosMethod sumObject busdaycalendarMethod is_busdayProperty dtypeMethod uniqueMethod loadtxtMethod vsplitMethod fliplrMethod setdiff1dMethod msortMethod argsortMethod lexsortMethod aroundMethod nanmaxMethod nanminMethod nanargmaxMethod nanargminMethod argmaxMethod argminProperty itemsizeMethod spacingMethod fixMethod ceilMethod diffProperty flatProperty realProperty baseMethod flipMethod deleteMethod amaxMethod aminMethod logical_xorMethod logical_orMethod logical_notMethod logical_andMethod logaddexpMethod logaddexp2Method logspaceMethod not_equalMethod equalMethod greater_equalMethod lessMethod less_equalMethod remainderMethod modMethod emptyMethod greaterMethod isfiniteMethod busday_countMethod repeatMethod varMethod random_sampleMethod randomMethod signMethod stdMethod absoluteMethod absMethod sortMethod randintMethod isrealMethod linspaceMethod gradientMethod allMethod sampleProperty TProperty imagMethod covMethod insertMethod logMethod log1pMethod exp2Method expm1Method expMethod arccosMethod cosMethod arcsinMethod sinMethod tanMethod fromiterMethod trim_zerosMethod diagflatMethod savetxtMethod count_nonzeroProperty sizeProperty shapeMethod reshapeMethod resizeMethod triuMethod trilMethod eyeMethod arangeMethod fill_diagonalMethod tileMethod saveMethod transposeMethod swapaxesMethod meshgridProperty mgridMethod rot90Method log2Method radiansMethod deg2radMethod rad2degMethod degreesMethod log10Method appendMethod cumprodProperty nbytesMethod tostringProperty dataMethod modfMethod fmodMethod tolistMethod datetime_as_stringMethod datetime_dataMethod array_splitMethod itemsetMethod floorMethod put_along_axisMethod cumsumMethod bincountMethod putMethod putmaskMethod takeMethod hypotMethod sqrtMethod squareMethod floor_divideMethod triMethod signbitMethod flattenMethod ravelMethod rollMethod isrealobjMethod diagMethod diagonalMethod quantileMethod onesMethod iscomplexobjMethod iscomplexMethod isscalarMethod divmodMethod isnatMethod percentileMethod isnanMethod divideMethod addMethod reciprocalMethod positiveMethod subtractMethod medianMethod isneginfMethod isposinfMethod float_powerMethod powerMethod negativeMethod maximumMethod averageMethod isinfMethod multiplyMethod busday_offsetMethod identityMethod interpMethod squeezeMethod get_printoptionsMethod savez_compressedMethod savezMethod loadMethod asfarrayMethod clipMethod arrayMethod array_equivMethod array_equalMethod frombufferMethod set_string_functionMethod matmulMethod genfromtxtMethod fromfunctionMethod asscalarMethod searchsortedMethod full_likeMethod fullMethod shares_memoryMethod ptpMethod digitizeMethod argwhereMethod geomspaceMethod zeros_likeMethod fabsMethod flatnonzeroMethod vstackMethod dstackMethod fromstringMethod tobytesMethod expand_dimsMethod ranfMethod arctanMethod itemMethod extractMethod compressMethod chooseMethod asarrayMethod asmatrixMethod allcloseMethod iscloseMethod anyMethod corrcoefMethod truncMethod prodMethod crossMethod true_divideMethod hsplitMethod splitMethod rintMethod ediff1dMethod lcmMethod gcdMethod cbrtMethod flipudProperty ndimMethod array2stringMethod set_printoptionsMethod whereMethod hstack
Char32 topics
Comments
Log in or sign up
Cancel
Post
account_circle
Profile
exit_to_app
Sign out
help Ask a question
Share on Twitter
search
keyboard_voice
close
Searching Tips
Search for a recipe: "Creating a table in MySQL"
Search for an API documentation: "@append"
Search for code: "!dataframe"
Apply a tag filter: "#python"
Useful Shortcuts
/ to open search panel
Esc to close search panel
to navigate between search results
d to clear all current filters
Enter to expand content preview
icon_star
Doc Search
icon_star
Code Search Beta
SORRY NOTHING FOUND!
mic
Start speaking...
Voice search is only supported in Safari and Chrome.
Navigate to
A
A
share
thumb_up_alt
bookmark
arrow_backShare
Twitter
Facebook
chevron_left Documentation
Method argpartition
NumPy Random Generator4 topics
Method choiceMethod dotMethod finfoMethod histogramMethod iinfoMethod maxMethod meanMethod placeMethod rootsMethod seedMethod uniformMethod viewMethod zerosMethod sumObject busdaycalendarMethod is_busdayProperty dtypeMethod uniqueMethod loadtxtMethod vsplitMethod fliplrMethod setdiff1dMethod msortMethod argsortMethod lexsortMethod aroundMethod nanmaxMethod nanminMethod nanargmaxMethod nanargminMethod argmaxMethod argminProperty itemsizeMethod spacingMethod fixMethod ceilMethod diffProperty flatProperty realProperty baseMethod flipMethod deleteMethod amaxMethod aminMethod logical_xorMethod logical_orMethod logical_notMethod logical_andMethod logaddexpMethod logaddexp2Method logspaceMethod not_equalMethod equalMethod greater_equalMethod lessMethod less_equalMethod remainderMethod modMethod emptyMethod greaterMethod isfiniteMethod busday_countMethod repeatMethod varMethod random_sampleMethod randomMethod signMethod stdMethod absoluteMethod absMethod sortMethod randintMethod isrealMethod linspaceMethod gradientMethod allMethod sampleProperty TProperty imagMethod covMethod insertMethod logMethod log1pMethod exp2Method expm1Method expMethod arccosMethod cosMethod arcsinMethod sinMethod tanMethod fromiterMethod trim_zerosMethod diagflatMethod savetxtMethod count_nonzeroProperty sizeProperty shapeMethod reshapeMethod resizeMethod triuMethod trilMethod eyeMethod arangeMethod fill_diagonalMethod tileMethod saveMethod transposeMethod swapaxesMethod meshgridProperty mgridMethod rot90Method log2Method radiansMethod deg2radMethod rad2degMethod degreesMethod log10Method appendMethod cumprodProperty nbytesMethod tostringProperty dataMethod modfMethod fmodMethod tolistMethod datetime_as_stringMethod datetime_dataMethod array_splitMethod itemsetMethod floorMethod put_along_axisMethod cumsumMethod bincountMethod putMethod putmaskMethod takeMethod hypotMethod sqrtMethod squareMethod floor_divideMethod triMethod signbitMethod flattenMethod ravelMethod rollMethod isrealobjMethod diagMethod diagonalMethod quantileMethod onesMethod iscomplexobjMethod iscomplexMethod isscalarMethod divmodMethod isnatMethod percentileMethod isnanMethod divideMethod addMethod reciprocalMethod positiveMethod subtractMethod medianMethod isneginfMethod isposinfMethod float_powerMethod powerMethod negativeMethod maximumMethod averageMethod isinfMethod multiplyMethod busday_offsetMethod identityMethod interpMethod squeezeMethod get_printoptionsMethod savez_compressedMethod savezMethod loadMethod asfarrayMethod clipMethod arrayMethod array_equivMethod array_equalMethod frombufferMethod set_string_functionMethod matmulMethod genfromtxtMethod fromfunctionMethod asscalarMethod searchsortedMethod full_likeMethod fullMethod shares_memoryMethod ptpMethod digitizeMethod argwhereMethod geomspaceMethod zeros_likeMethod fabsMethod flatnonzeroMethod vstackMethod dstackMethod fromstringMethod tobytesMethod expand_dimsMethod ranfMethod arctanMethod itemMethod extractMethod compressMethod chooseMethod asarrayMethod asmatrixMethod allcloseMethod iscloseMethod anyMethod corrcoefMethod truncMethod prodMethod crossMethod true_divideMethod hsplitMethod splitMethod rintMethod ediff1dMethod lcmMethod gcdMethod cbrtMethod flipudProperty ndimMethod array2stringMethod set_printoptionsMethod whereMethod hstack
Char32 topics
thumb_up
0
thumb_down
0
chat_bubble_outline
0
auto_stories new
settings

NumPy | var method

Programming
chevron_right
Python
chevron_right
NumPy
chevron_right
Documentation
schedule Mar 10, 2022
Last updated
local_offer PythonNumPy
Tags

NumPy's var(~) method computes the variance of values in the input array. The variance is computed using the following formula:

$$\frac{1}{N}\sum_{i=0}^{N}\left(x_i-\bar{x}^2\right)$$

Where:

  • $N$ is the size of the given array (i.e. the sample size)

  • $x_i$ is the value of the $i$th index in the Numpy array

  • $\bar{x}$ is the sample mean

NOTE

var(~) method can also compute the unbiased estimate of the variance. We do this by setting ddof=1 in the parameters, as we shall see later in the examples.

Parameters

1. a | array-like

The array on which to perform the method.

2. axislink | int or tuple | optional

The axis along which we compute the variance. For 2D arrays, the allowed values are as follows:

Axis

Meaning

0

Variance will be computed column-wise

1

Variance will be computed row-wise

None

Variance will be computed on a flattened array

By default, axis=None.

3. dtype | string or type | optional

The type used to compute the variance. If the input array is of type int, then float32 will be used. If the input array is of another numerical type, then its type will be used.

4. ddoflink | int | optional

The delta degree of freedom. This can be used to modify the denominator in the front:

$$\frac{1}{N\color{blue}{-ddof}}\sum_{i=0}^{N}\left(x_i-\bar{x}^2\right)$$

By default, ddof=0.

Return value

If axis=None, then a single float representing the variance of all the values in the array is returned. Otherwise, a Numpy array is returned.

Examples

Variance of a 1D array

np.var([1,2,3,4])
1.25

Computing sample variance

To compute the sample variance, set ddof=1:

np.var([1,2,3,4], ddof=1)
1.6666666666666667

Computing population variance

To compute the population variance, leave out the ddof parameter or explicitly set ddof=0:

np.var([1,2,3,4])   # By default, ddof=0
1.25

Variance of a 2D array

Entire array

Without specifying the axis parameter, Numpy will just regard your Numpy array as a flattened array.

np.var([[1,2],[3,4]])
1.25

This code is fundamentally the same as np.var([1,2,3,4]).

Column-wise

To compute the variance column-wise, specify axis=0 in the parameters:

np.var([[1,4],[2,6], [3,8]], axis=0)
array([0.66666667, 2.66666667])

Here, we're computing the variance of [1,2,3] (i.e. the first column) as well as [4,6,8] (i.e. the second column).

Row-wise

To compute the variance column-wise, specify axis=1 in the parameters:

np.var([[1,4],[2,6], [3,8]], axis=1)
array([2.25, 4. , 6.25])

Here, we're computing three variances: first row (i.e. [1,4]), second row (i.e. [2,6]) and third row (i.e. [3,8]).

WARNING

Sometimes the numerical type float32 may not be accurate enough for your needs. If your application requires more accurate numbers, then set dtype=np.float64 in the argument. This will take up more memory, but will provide a more accurate result.

robocat
Published by Isshin Inada
Edited by 0 others
Did you find this page useful?
thumb_up
thumb_down
Ask a question or leave a feedback...