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import pandas as pd | ||
import os | ||
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paths_to_clean = [ | ||
os.path.join('full_Study','complete_study_mar16.csv'), | ||
os.path.join('full_Study','study.csv'), | ||
os.path.join('full_Study','data_patch.csv'), | ||
os.path.join('full_Study','data_clean.csv'), | ||
os.path.join('full_Study','data_clean_june30.csv'), | ||
os.path.join('full_Study','condition_count.csv'), | ||
os.path.join('pilot2','Complexity vs. Trust in Vis_March 6, 2023_07.54.csv'), | ||
os.path.join('pilot3','pilot3.csv'), | ||
os.path.join('pilot3','pilot3_clean.csv'), | ||
os.path.join('pilot3','Complexity vs. Trust in Vis_March 12, 2023_16.46.csv'), | ||
os.path.join('pilot3','Complexity vs. Trust in Vis_March 12, 2023_16.47.csv'), | ||
os.path.join('pilot4','data.csv'), | ||
os.path.join('pilot4','data_patch.csv'), | ||
os.path.join('replicationStudy','data.csv'), | ||
os.path.join('replicationStudy','data_clean.csv') | ||
] | ||
for path in paths_to_clean: | ||
df = pd.read_csv(path) | ||
print('Interview_1_TEXT' in df.columns) | ||
df = df.drop('Interview_1_TEXT',axis=1) | ||
df.to_csv(path,index=False) | ||
# for col in df.columns: | ||
# print(col) | ||
# print(df['Interview_1_TEXT']) |
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