A quick way to know the pandas version number
A quick way to understand pandas version numbers requires specific code examples
Overview:
Pandas is a popular Python library for data analysis and data deal with. Knowing the version number of Pandas is very important to ensure the compatibility and stability of your code. This article will introduce how to quickly obtain the version number of Pandas and provide specific code examples.
The importance of Pandas version number:
The version number of Pandas contains a lot of useful information, such as fixed bugs, new features introduced, and API changes. Therefore, when we write code, knowing the Pandas version number currently used can help us avoid problems due to version mismatch.
Method 1: Use the install_info() function
We can use the install_info() function that comes with the Pandas library to obtain detailed Pandas version information. This function will return a dictionary containing the Pandas version number and other related information.
import pandas as pd info = pd.install_info() print(info['INSTALLED VERSIONS']['pandas'])
Running the above code will output the currently installed Pandas version number.
Method 2: Use the __version__ attribute
Another way to get the Pandas version number is to use the __version__ attribute of the Pandas library. This property directly returns a string representation of the current Pandas version.
import pandas as pd print(pd.__version__)
Running the above code will output the currently installed Pandas version number.
Example:
Assuming that our code depends on Pandas version 0.25.3 and above, we can use the following code to check whether the current Pandas version meets the requirements:
import pandas as pd pandas_version = pd.__version__ required_version = '0.25.3' if pandas_version >= required_version: print("当前Pandas版本符合要求") else: print("当前Pandas版本不符合要求,请升级至0.25.3或更高版本")
Summary:
Knowing the Pandas version number currently in use is very important for writing stable and compatible code. This article introduces two methods to quickly obtain the Pandas version number and gives specific code examples. By using these methods, we can accurately check the Pandas version number when writing code, thus avoiding problems caused by version mismatch.
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