Tutorial 1 - Import/Convert/Export Data#

[1]:
import pydpeet as eet

eet.set_logging_style("ERROR")

Optionally set a logging_style to show additional Infos (Useful when running heavy workloads to see the progress)

[2]:
# eet.utils.set_logging_style(level="INFO", formatting_string="%(levelname)s | %(pathname)s:%(lineno)d | %(message)s")

Convert/Import Single files into a unified Dataframe for easy and fast Processing and Analysis

[3]:
Data = eet.read(config="neware_8_0_0_516", input_path=r"..\..\res\raw\Cal_Ageing_Checkup1.xlsx")
Data.head()
[3]:
Meta_Data Step_Count Voltage[V] Current[A] Temperature[°C] Test_Time[s] Date_Time EIS_f[Hz] EIS_Z_Real[Ohm] EIS_Z_Imag[Ohm] EIS_DC[A]
0.0 20240201100904-CheckUp-3-7-AM23NMC00009.xlsx U... 0 3.5269 1.4378 27.8 0.0 2024-02-01 10:09:04 None None None None
1.0 None 0 3.5287 1.4398 27.8 1.0 2024-02-01 10:09:05 None None None None
2.0 None 0 3.5298 1.4400 27.8 2.0 2024-02-01 10:09:06 None None None None
3.0 None 0 3.5307 1.4400 27.8 3.0 2024-02-01 10:09:07 None None None None
4.0 None 0 3.5315 1.4401 27.8 4.0 2024-02-01 10:09:08 None None None None

Overwrite the previous logging_style to only show Warnings and Errors following the default format

[4]:
# eet.utils.set_logging_style()

Convert/Import files from one directory into a list of Dataframe or when you give and export path it gets directly exortet as parquet file.

[5]:
Datas = eet.read(config="neware_8_0_0_516", input_path=r"..\..\res\raw")

After youre work is done you can export youre unifed and/or analyzed file.

[6]:
eet.write(Data, output_path=r"C:\temp\test", output_file_name="Test")  # todo: export files and list of files