<jupyter_start><jupyter_text>At this point, I like to open the sheet and clean it up:1. Delete the empty "Sheet1" default table, or else rename it and repurpose it for whatever (e.g., pasting in a Gaia EDR3 cross-match).2. Go to "Targets" and bold the column names, then go to View>Freeze>1row to lock it in place so you can see columns while scrolling down. You can do these things from python here, but I haven't coded that in.<jupyter_code># Once the Sheet is populated, you can download the TESS FFI data. This will create a number of subfolders in the project folder.
# I'm setting a brighter threshold to reduce the number of files downloaded while testing
tess_tools.download_tess(project_name,mag_cut=16.0)
# This will use the FFIs to create CPM light curves, saved as *csv files stored in the Projects/[project]/CPM/ folder.

tess_tools.make_cpm(project_name)
# This will use the FFIs to create SAP light curves (simple aperture photometry), saved as *csv files stored in the Projects/[project]/SAP/ folder.
tess_tools.make_sap(project_name)<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.06574074074074074, 'fraction_numerical': 0.007407407407407408, 'mean_word_length': 4.972375690607735, 'pattern_counts': {'":': 0, '<': 5, '<?xml version=': 0, '>': 7, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 3, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
{'chain_length': '1', 'dir': 'jupyter-structured-clean-dedup', 'id': '106615', 'license': 'MIT', 'n_tokens_mistral': 334, 'n_tokens_neox': 313, 'n_words': 155, 'path': 'TESS_Prep.ipynb', 'repo_name': 'stephtdouglas/tess_check', 'size': '1080'}