I have around 10 csv files in my folder. I want to create a 1:1 merge on one common column, called "ACCESS_ID"
.
After specifying the path directory, I create a DataFrame to put all the local csv files in:
os.chdir('C:/Users/xx/Downloads/merge/')
csvs_all = pd.DataFrame()
I can individually read in all the .csv files using pd.read_csv()
function and store all the dataframes to a list, but I am trying to automate the process as much as possible.
for f in glob.glob('C:/Users/xx/Downloads/merge/*.csv'):
df = pd.read_csv(f)
csvs_all=pd.concat([dfs,df])
This code is not working and is creating multiple duplicate entries. Some of the column entries are exhibiting NA
values. Is there a way to use pd.merge
on multiple datasets/csv files? I would like to do the following:
csvs_all = pd.merge([all my csv files], on='ACCESS_ID')