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Formatting Float64Index in Pandas DataFrame

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by vsasikalabe dot icon Updated: Jan 30, 2023

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In a Pandas DataFrame, the Float64Index is the index (or row label) of the DataFrame of data type float64. Formatting the Float64Index in a Pandas DataFrame can be useful in various applications, including data analysis and visualization. Here are a few examples:  

  • Data Analysis: Formatting the index as a percentage can make it easier to compare values across different rows in the DataFrame, especially when the values are large or small.  
  • Data Visualization: When creating charts or graphs from the DataFrame, formatting the index as a percentage can make the axis labels more readable and intuitive for the audience.  
  • Reporting: When creating reports or summaries of the data, formatting the index as a percentage can make it easier to convey the information to the audience clearly and concisely.  
  • Data Cleaning: Sometimes, the index may contain unwanted data that is not useful for the analysis; in that case, formatting can be applied to get the required data.  
  • Data Transformation: Formatting the index can also be used as a pre-processing step to transform the data into a more usable format for further analysis.  


Here is how you can format Float64Index in a Pandas DataFrame:  

Preview of the output that you will get on running this code from your IDE.

Code

In this solution we used pandas and numpy library of python.

Formatting Float64Index in Pandas DataFrame

PythondotLines of Code : 23dotLicense : Strong Copyleft (CC BY-SA 4.0)

Dependent Libraries : 
df.index = df.index.astype(int)

df = pd.DataFrame({'a':[1,2,3]}, index=[2011,2012,np.nan])
print (df)
         a
 2011.0  1
 2012.0  2
NaN      3

df.index = df.index.fillna(1970).astype(int)
print (df)
      a
2011  1
2012  2
1970  3

df = df[df.index.notnull()]
df.index = df.index.astype(int)
print (df)
      a
2011  1
2012  2

Instructions

Follow the steps carefully to get the output easily.

  1. Download and Install the PyCharm Community Edition on your computer.
  2. Install pandas and numpy on your IDE from python interpreter in setting options.
  3. Create new python file on your IDE.
  4. Copy the snippet using the 'copy' button and paste it in your python file.
  5. Import Pandas and numpy library.
  6. Run the current file to generate the output.


I hope you found this useful. I have added the link to dependent libraries, version information in the following sections.


I found this code snippet by searching for ' Formatting Float64Index in Pandas DataFrame' in kandi. You can try any such use case!

Environment Tested

I tested this solution in the following versions. Be mindful of changes when working with other versions.

  1. The solution is created in PyCharm 2022.3.
  2. The solution is tested on Python 3.11.1
  3. Pandas version-1.5.2.
  4. numpy version 1.24.0.


Using this solution, we are able to Formatting Float64Index in Pandas DataFrame with simple steps. This process also facilities an easy way to use, hassle-free method to create a hands-on working version of code which would help us to Formatting Float64Index in Pandas DataFrame.

Dependent Libraries

pandasby pandas-dev

Python doticonstar image 38689 doticonVersion:v2.0.2doticon
License: Permissive (BSD-3-Clause)

Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more

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            pandasby pandas-dev

            Python doticon star image 38689 doticonVersion:v2.0.2doticon License: Permissive (BSD-3-Clause)

            Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more
            Support
              Quality
                Security
                  License
                    Reuse

                      numpyby numpy

                      Python doticonstar image 23755 doticonVersion:v1.25.0rc1doticon
                      License: Permissive (BSD-3-Clause)

                      The fundamental package for scientific computing with Python.

                      Support
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                            License
                              Reuse

                                numpyby numpy

                                Python doticon star image 23755 doticonVersion:v1.25.0rc1doticon License: Permissive (BSD-3-Clause)

                                The fundamental package for scientific computing with Python.
                                Support
                                  Quality
                                    Security
                                      License
                                        Reuse

                                          If you do not have pandas library that is required to run this code, you can install it by clicking on the above link.

                                          You can search for any dependent library on kandi like pandas and numpy.

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