I am trying to take multiple data files with the same number of columns into one continuous set of data. The x values are time and each subsequent datafile starts at the time of the previous one finishing. So in theory if I do some code like this:
data = pd.read_csv(r"/PATH/out.txt", sep="\t")
data2 = pd.read_csv(r"/PATH/out2.txt", sep="\t")
data3 = pd.read_csv(r"/PATH/out3.txt", sep="\t")
data4 = pd.read_csv(r"/PATH/out4.txt", sep="\t")
data5 = pd.read_csv(r"/PATH/out5.txt", sep="\t")
data6 = pd.read_csv(r"/PATH/out6.txt", sep="\t")
data7 = pd.read_csv(r"/PATH/out7.txt", sep="\t")
data8 = pd.read_csv(r"/PATH/out8.txt", sep="\t")
print(data)
data.append(data2, ignore_index=True)
data.append(data3, ignore_index=True)
data.append(data4, ignore_index=True)
data.append(data5, ignore_index=True)
data.append(data6, ignore_index=True)
data.append(data7, ignore_index=True)
data.append(data8, ignore_index=True)
print(data)
arr = data.to_numpy()
The print statement before and after should be different right? But it doesnt appear to append the other data files to the first one when I try. I must be missing something obvious, can anyone help with this?
The data files are in a 2 column format and look something like this (leftmost column is just the pandas indexing):
Time(s) CMASS(1,1,53)
0 97.000229 0.999999
1 98.000183 0.999999
2 98.001122 0.999999
3 98.200874 0.999999
4 98.400703 0.999999
.. ... ...
209 119.700410 0.999999
210 119.800410 0.999999
211 119.900410 0.999999
212 120.000400 0.999999
213 120.000400 0.999999