column assignment doesn't support type range

Dask “Column assignment doesn’t support type numpy.ndarray”

I’m trying to use Dask instead of pandas since the data size I’m analyzing is quite large. I wanted to add a flag column based on several conditions.

But, then I got the following error message. The above code works perfectly when using np.where with pandas dataframe, but didn’t work with dask.array.where .

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If numpy works and the operation is row-wise, then one solution is to use .map_partitions :

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<input type="range">

<input> elements of type range let the user specify a numeric value which must be no less than a given value, and no more than another given value. The precise value, however, is not considered important. This is typically represented using a slider or dial control rather than a text entry box like the number input type.

Because this kind of widget is imprecise, it should only be used if the control's exact value isn't important.

If the user's browser doesn't support type range , it will fall back and treat it as a text input.

There is no pattern validation available; however, the following forms of automatic validation are performed:

• If the value is set to something which can't be converted into a valid floating-point number, validation fails because the input is suffering from a bad input.
• The value won't be less than min . The default is 0.
• The value won't be greater than max . The default is 100.
• The value will be a multiple of step . The default is 1.

The value attribute contains a string which contains a string representation of the selected number. The value is never an empty string ( "" ). The default value is halfway between the specified minimum and maximum—unless the maximum is actually less than the minimum, in which case the default is set to the value of the min attribute. The algorithm for determining the default value is:

If an attempt is made to set the value lower than the minimum, it is set to the minimum. Similarly, an attempt to set the value higher than the maximum results in it being set to the maximum.

Additional attributes

In addition to the attributes shared by all <input> elements, range inputs offer the following attributes.

Note: The following input attributes do not apply to the input range: accept , alt , checked , dirname , formaction , formenctype , formmethod , formnovalidate , formtarget , height , maxlength , minlength , multiple , pattern , placeholder , readonly , required , size , and src . Any of these attributes, if included, will be ignored.

The value of the list attribute is the id of a <datalist> element located in the same document. The <datalist> provides a list of predefined values to suggest to the user for this input. Any values in the list that are not compatible with the type are not included in the suggested options. The values provided are suggestions, not requirements: users can select from this predefined list or provide a different value.

See the adding tick marks below for an example of how the options on a range are denoted in supported browsers.

The greatest value in the range of permitted values. If the value entered into the element exceeds this, the element fails constraint validation . If the value of the max attribute isn't a number, then the element has no maximum value.

This value must be greater than or equal to the value of the min attribute. See the HTML max attribute.

The lowest value in the range of permitted values. If the value of the element is less than this, the element fails constraint validation . If a value is specified for min that isn't a valid number, the input has no minimum value.

This value must be less than or equal to the value of the max attribute. See the HTML min attribute.

Note: If the min and max values are equal or the max value is lower than the min value the user will not be able to interact with the range.

The step attribute is a number that specifies the granularity that the value must adhere to. Only values that match the specified stepping interval ( min if specified, value otherwise, or an appropriate default value if neither of those is provided) are valid.

The step attribute can also be set to the any string value. This step value means that no stepping interval is implied and any value is allowed in the specified range (barring other constraints, such as min and max ). See the Setting step to the any value example for how this works in supported browsers.

Note: When the value entered by a user doesn't adhere to the stepping configuration, the user agent may round off the value to the nearest valid value, preferring to round numbers up when there are two equally close options.

The default stepping value for range inputs is 1, allowing only integers to be entered, unless the stepping base is not an integer; for example, if you set min to -10 and value to 1.5, then a step of 1 will allow only values such as 1.5, 2.5, 3.5,… in the positive direction and -0.5, -1.5, -2.5,… in the negative direction. See the HTML step attribute .

Non-standard attributes

Similar to the -moz-orient non-standard CSS property impacting the <progress> and <meter> elements, the orient attribute defines the orientation of the range slider. Values include horizontal , meaning the range is rendered horizontally, and vertical , where the range is rendered vertically.

While the number type lets users enter a number with optional constraints forcing their value to be between a minimum and a maximum value, it does require that they enter a specific value. The range input type lets you ask the user for a value in cases where the user may not even care—or know—what the specific numeric value selected is.

A few examples of situations in which range inputs are commonly used:

• Audio controls such as volume and balance, or filter controls.
• Color configuration controls such as color channels, transparency, brightness, etc.
• Game configuration controls such as difficulty, visibility distance, world size, and so forth.
• Password length for a password manager's generated passwords.

As a rule, if the user is more likely to be interested in the percentage of the distance between minimum and maximum values than the actual number itself, a range input is a great candidate. For example, in the case of a home stereo volume control, users typically think "set volume at halfway to maximum" instead of "set volume to 0.5".

Specifying the minimum and maximum

By default, the minimum is 0 and the maximum is 100. If that's not what you want, you can easily specify different bounds by changing the values of the min and/or max attributes. These can be any floating-point value.

For example, to ask the user for a value between -10 and 10, you can use:

Setting the value's granularity

By default, the granularity is 1, meaning the value is always an integer. To control the granularity, you can change the step attribute. For example, If you need a value to be halfway between 5 and 10, you should set the value of step to 0.5:

Setting the step attribute

Setting step to any.

If you want to accept any value regardless of how many decimal places it extends to, you can specify a value of any for the step attribute:

This example lets the user select any value between 0 and π without any restriction on the fractional part of the value selected. JavaScript is used to show how the value changes as the user interacts with the range.

Adding tick marks

To add tick marks to a range control, include the list attribute, giving it the id of a <datalist> element which defines a series of tick marks on the control. Each point is represented using an <option> element with its value set to the range's value at which a mark should be drawn.

Using the same datalist for multiple range controls

To help you from repeating code you can reuse that same <datalist> for multiple <input type="range"> elements, and other <input> types.

Note: If you also want to show the labels as in the example below then you would need a datalist for each range input.

Adding labels

You can label tick marks by giving the <option> elements label attributes. However, the label content will not be displayed by default. You can use CSS to show the labels and to position them correctly. Here's one way you could do this.

Creating vertical range controls

By default, browsers render range inputs as sliders with the knob sliding left and right.

To create a vertical range wherein the thumb slides up and down, set the writing-mode property with a value of either vertical-rl or vertical-lr :

This causes the range slider to render vertically:

You can also set the CSS appearance property to the non-standard slider-vertical value if you want to support older versions of Chrome and Safari, and include the non-standard orient="vertical" attribute to support older versions of Firefox.

See Creating vertical form controls for examples.

Technical summary

Specifications, browser compatibility.

BCD tables only load in the browser with JavaScript enabled. Enable JavaScript to view data.

• <input> and the HTMLInputElement interface it's based upon
• <input type="number">
• validityState.rangeOverflow and validityState.rangeUnderflow
• Controlling multiple parameters with ConstantSourceNode
• Creating vertical form controls
• Styling the range element
• Compatibility of CSS properties

Type Support in Pandas API on Spark ¶

In this chapter, we will briefly show you how data types change when converting pandas-on-Spark DataFrame from/to PySpark DataFrame or pandas DataFrame.

Type casting between PySpark and pandas API on Spark ¶

When converting a pandas-on-Spark DataFrame from/to PySpark DataFrame, the data types are automatically casted to the appropriate type.

The example below shows how data types are casted from PySpark DataFrame to pandas-on-Spark DataFrame.

The example below shows how data types are casted from pandas-on-Spark DataFrame to PySpark DataFrame.

Type casting between pandas and pandas API on Spark ¶

When converting pandas-on-Spark DataFrame to pandas DataFrame, and the data types are basically same as pandas.

However, there are several data types only provided by pandas.

These kind of pandas specific data types below are not currently supported in pandas API on Spark but planned to be supported.

pd.Timedelta

pd.Categorical

pd.CategoricalDtype

The pandas specific data types below are not planned to be supported in pandas API on Spark yet.

pd.SparseDtype

pd.DatetimeTZDtype

pd.UInt*Dtype

pd.BooleanDtype

pd.StringDtype

Internal type mapping ¶

The table below shows which NumPy data types are matched to which PySpark data types internally in pandas API on Spark.

The table below shows which Python data types are matched to which PySpark data types internally in pandas API on Spark.

For decimal type, pandas API on Spark uses Spark’s system default precision and scale.

You can check this mapping by using as_spark_type function.

You can also check the underlying PySpark data type of Series or schema of DataFrame by using Spark accessor.

Pandas API on Spark currently does not support multiple types of data in single column.

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Python typeerror: ‘tuple’ object does not support item assignment Solution

Tuples are immutable objects . “Immutable” means you cannot change the values inside a tuple. You can only remove them. If you try to assign a new value to an item in a variable, you’ll encounter the “typeerror: ‘tuple’ object does not support item assignment” error.

In this guide, we discuss what this error means and why you may experience it. We’ll walk through an example of this error so you can learn how to solve it in your code.

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Typeerror: ‘tuple’ object does not support item assignment.

While tuples and lists both store sequences of data, they have a few distinctions. Whereas you can change the values in a list, the values inside a tuple cannot be changed. Also, tuples are stored within parenthesis whereas lists are declared between square brackets.

Because you cannot change values in a tuple, item assignment does not work.

Consider the following code snippet:

This code snippet lets us change the first value in the “honor_roll” list to Holly. This works because lists are mutable. You can change their values. The same code does not work with data that is stored in a tuple.

An Example Scenario

Let’s build a program that tracks the courses offered by a high school. Students in their senior year are allowed to choose from a class but a few classes are being replaced.

Start by creating a collection of class names:

We’ve created a tuple that stores the names of each class being offered.

The science department has notified the school that psychology is no longer being offered due to a lack of numbers in the class. We’re going to replace psychology with philosophy as the philosophy class has just opened up a few spaces.

To do this, we use the assignment operator:

This code will replace the value at the index position 3 in our list of classes with “Philosophy”. Next, we print our list of classes to the console so that the user can see what classes are being actively offered:

Use a for loop to print out each class in our tuple to the console. Let’s run our code and see what happens:

Our code returns an error.

The Solution

We’ve tried to use the assignment operator to change a subject in our list. Tuples are immutable so we cannot change their values. This is why our code returns an error.

To solve this problem, we convert our “classes” tuple into a list . This will let us change the values in our sequence of class names.

Do this using the list() method:

We use the list() method to convert the value of “classes” to a list. We assign this new list to the variable “as_list”. Now that we have our list of classes stored as a list, we can change existing classes in the list.

Let’s run our code:

Our code successfully changes the “Psychology” class to “Philosophy”. Our code then prints out the list of classes to the console.

If we need to store our data as a tuple, we can always convert our list back to a tuple once we have changed the values we want to change. We can do this using the tuple() method:

This code converts “as_list” to a tuple and prints the value of our tuple to the console:

We could use this tuple later in our code if we needed our class names stored as a tuple.

The “typeerror: ‘tuple’ object does not support item assignment” error is raised when you try to change a value in a tuple using item assignment.

To solve this error, convert a tuple to a list before you change the values in a sequence. Optionally, you can then convert the list back to a tuple.

Now you’re ready to fix this error in your code like a pro !

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[Solved] TypeError: ‘str’ Object Does Not Support Item Assignment

In this article, we will be discussing the TypeError:’str’ Object Does Not Support Item Assignment exception . We will also be going through solutions to this problem with example programs.

Why is This Error Raised?

When you attempt to change a character within a string using the assignment operator, you will receive the Python error TypeError: ‘str’ object does not support item assignment.

As we know, strings are immutable. If you attempt to change the content of a string, you will receive the error TypeError: ‘str’ object does not support item assignment .

There are four other similar variations based on immutable data types :

• TypeError: 'tuple' object does not support item assignment
• TypeError: 'int' object does not support item assignment
• TypeError: 'float' object does not support item assignment
• TypeError: 'bool' object does not support item assignment

Replacing String Characters using Assignment Operators

Replicate these errors yourself online to get a better idea here .

In this code, we will attempt to replace characters in a string.

Strings are an immutable data type. However, we can change the memory to a different set of characters like so:

TypeError: ‘str’ Object Does Not Support Item Assignment in JSON

Let’s review the following code, which retrieves data from a JSON file.

In line 5, we are assigning data['sample'] to a string instead of an actual dictionary. This causes the interpreter to believe we are reassigning the value for an immutable string type.

TypeError: ‘str’ Object Does Not Support Item Assignment in PySpark

The following program reads files from a folder in a loop and creates data frames.

This occurs when a PySpark function is overwritten with a string. You can try directly importing the functions like so:

TypeError: ‘str’ Object Does Not Support Item Assignment in PyMongo

The following program writes decoded messages in a MongoDB collection. The decoded message is in a Python Dictionary.

At the 10th visible line, the variable x is converted as a string.

It’s better to use:

Please note that msg are a dictionary and NOT an object of context.

TypeError: ‘str’ Object Does Not Support Item Assignment in Random Shuffle

The below implementation takes an input main and the value is shuffled. The shuffled value is placed into Second .

random.shuffle is being called on a string, which is not supported. Convert the string type into a list and back to a string as an output in Second

TypeError: ‘str’ Object Does Not Support Item Assignment in Pandas Data Frame

The following program attempts to add a new column into the data frame

The iteration statement for dataset in df: loops through all the column names of “sample.csv”. To add an extra column, remove the iteration and simply pass dataset['Column'] = 1 .

These are the causes for TypeErrors : – Incompatible operations between 2 operands: – Passing a non-callable identifier – Incorrect list index type – Iterating a non-iterable identifier.

The data types that support item assignment are: – Lists – Dictionaries – and Sets These data types are mutable and support item assignment

As we know, TypeErrors occur due to unsupported operations between operands. To avoid facing such errors, we must: – Learn Proper Python syntax for all Data Types. – Establish the mutable and immutable Data Types. – Figure how list indexing works and other data types that support indexing. – Explore how function calls work in Python and various ways to call a function. – Establish the difference between an iterable and non-iterable identifier. – Learn the properties of Python Data Types.

We have looked at various error cases in TypeError:’str’ Object Does Not Support Item Assignment. Solutions for these cases have been provided. We have also mentioned similar variations of this exception.

Trending Python Articles

TypeError: 'tuple' object does not support item assignment

Last updated: Apr 8, 2024 Reading time · 4 min

# TypeError: 'tuple' object does not support item assignment

The Python "TypeError: 'tuple' object does not support item assignment" occurs when we try to change the value of an item in a tuple.

To solve the error, convert the tuple to a list, change the item at the specific index and convert the list back to a tuple.

Here is an example of how the error occurs.

We tried to update an element in a tuple, but tuple objects are immutable which caused the error.

# Convert the tuple to a list to solve the error

We cannot assign a value to an individual item of a tuple.

Instead, we have to convert the tuple to a list.

This is a three-step process:

• Use the list() class to convert the tuple to a list.
• Update the item at the specified index.
• Use the tuple() class to convert the list back to a tuple.

Once we have a list, we can update the item at the specified index and optionally convert the result back to a tuple.

Python indexes are zero-based, so the first item in a tuple has an index of 0 , and the last item has an index of -1 or len(my_tuple) - 1 .

# Constructing a new tuple with the updated element

Alternatively, you can construct a new tuple that contains the updated element at the specified index.

The get_updated_tuple function takes a tuple, an index and a new value and returns a new tuple with the updated value at the specified index.

The original tuple remains unchanged because tuples are immutable.

We updated the tuple element at index 1 , setting it to Z .

If you only have to do this once, you don't have to define a function.

The code sample achieves the same result without using a reusable function.

The values on the left and right-hand sides of the addition (+) operator have to all be tuples.

The syntax for tuple slicing is my_tuple[start:stop:step] .

The start index is inclusive and the stop index is exclusive (up to, but not including).

If the start index is omitted, it is considered to be 0 , if the stop index is omitted, the slice goes to the end of the tuple.

# Using a list instead of a tuple

Alternatively, you can declare a list from the beginning by wrapping the elements in square brackets (not parentheses).

Declaring a list from the beginning is much more efficient if you have to change the values in the collection often.

Tuples are intended to store values that never change.

# How tuples are constructed in Python

In case you declared a tuple by mistake, tuples are constructed in multiple ways:

• Using a pair of parentheses () creates an empty tuple
• Using a trailing comma - a, or (a,)
• Separating items with commas - a, b or (a, b)
• Using the tuple() constructor

# Checking if the value is a tuple

You can also handle the error by checking if the value is a tuple before the assignment.

If the variable stores a tuple, we set it to a list to be able to update the value at the specified index.

The isinstance() function returns True if the passed-in object is an instance or a subclass of the passed-in class.

If you aren't sure what type a variable stores, use the built-in type() class.

The type class returns the type of an object.

# Additional Resources

You can learn more about the related topics by checking out the following tutorials:

• How to convert a Tuple to an Integer in Python
• How to convert a Tuple to JSON in Python
• Find Min and Max values in Tuple or List of Tuples in Python
• Get the Nth element of a Tuple or List of Tuples in Python
• Creating a Tuple or a Set from user Input in Python
• How to Iterate through a List of Tuples in Python
• Write a List of Tuples to a File in Python
• AttributeError: 'tuple' object has no attribute X in Python
• TypeError: 'tuple' object is not callable in Python [Fixed]

Borislav Hadzhiev

Web Developer

Copyright © 2024 Borislav Hadzhiev

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TypeError: 'range' object does not support item assignment #7

YangSN0719 commented Apr 15, 2019 • edited

YangSN0719 commented Apr 16, 2019

Sorry, something went wrong.

YangSN0719 commented Apr 16, 2019 • edited

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