brightwind.load.load.load_campbell_scientific

brightwind.load.load.load_campbell_scientific(filepath_or_folder, print_progress=True, **kwargs)

Load timeseries data from Campbell Scientific CR1000 formatted file, or group of files in a folder, into a DataFrame. If the file format is slightly different your own key word arguments can be sent as this is a wrapper around the pandas.read_csv function. The pandas.read_csv documentation can be found at: https://pandas.pydata.org/pandas-docs/stable/generated/pandas.read_csv.html

Parameters

• filepath_or_folder (str) – Location of the file folder containing the timeseries data.

• print_progress (bool, default True) – If you want to print out statements of the file been processed set to True. Default is True.

• kwargs – All the kwargs from pandas.read_csv can be passed to this function.

Returns

A DataFrame with timestamps as it’s index

Return type

pandas.DataFrame

When assembling files from folders into a single DataFrame with timestamp as the index it automatically checks for duplicates and throws an error if any found.

Example usage

import brightwind as bw
filepath = r'C:\some\folder\some_CR1000_data.csv'
df = bw.load_campbell_scientific(filepath)
print(df)

To load a group of files from a folder:

folder = r'C:\some\folder\with\CR1000\files'
df = bw.load_campbell_scientific(folder, print_progress=True)