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1: Importing Packages

1: Importing Packages#

1.1 Installing neonUtilities R Package#

To begin, we need to ensure that the neonUtilities package is installed. If you haven’t installed it previously, you can easily do so by following these steps:

from rpy2 import robjects
from rpy2.robjects.packages import importr
utils = importr('utils')
utils.install_packages('neonUtilities', repos='https://cran.rstudio.com/')
NOTE: This step is required only once. If you have already installed neonUtilities in R, you can skip this step.

1.2 Loading Necessary Packages#

Now that we have installed the required R package, let’s load the necessary Python packages for this tutorial. Run the following code to import the required libraries:

from rpy2.rinterface_lib.callbacks import logger as rpy2_logger
import logging
import os
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
from rpy2.robjects import r as base
from rpy2.robjects.packages import importr
# Set logging level to suppress R messages
rpy2_logger.setLevel(logging.ERROR)
# Load R's base, utils, and stats packages
base = importr('base')
utils = importr('utils')
stats = importr('stats')
# Importing R packages via rpy2
neonUtilities = importr('neonUtilities')
os.environ['R_HOME'] = '/Library/Frameworks/R.framework/Resources'

By using importr from rpy2, we import the core R packages base, utils, and stats for general-purpose operations within the R environment.

Key Points:

  • The neonUtilities package is installed within the R environment, not directly in Python.
  • rpy2 acts as a bridge, allowing Python to interact with R objects and packages.
  • Remember to adjust the R path if your installation differs from the provided example.

Next Steps:

We’ll proceed with using the neonUtilities package through rpy2 to access and process NEON data from Python. By following these steps, you’ll have a well-prepared Python environment to leverage the neonUtilities R package for analyzing NEON data in your Jupyter Notebook.

NOTE: Ensure that you have R installed on your system and the necessary paths are correctly configured. If you're using Jupyter Notebook, you can set the R home directory as shown in the last line of code above. This line ensures that Python can locate your R installation. If your R installation path is different, replace the provided path accordingly.

This section provides a structured approach to installing the neonUtilities package in R and importing the required Python packages for data processing. Ensure to execute these steps sequentially for a seamless experience with the tutorial.

Feel free to adjust the instructions or add any additional information to better suit your tutorial’s context.

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