I have 6 csv files like this:
A,5601093669
C,714840722
D,3311821086
E,3714631762
F,2359322409
G,4449445373
H,1321142307
I,3403144346
K,2941319082
L,5982421765
M,1431041943
N,2289666237
P,2944809622
Q,2266749163
R,3503618053
S,3995185703
T,3348978524
V,4184646229
W,790817778
Y,1747887712
And I would like to concatenate them side by side, ie:
A,5601093669,5601093669,5601093669,5601093669... C,714840722,714840722,714840722,714840722 ... D,3311821086,3311821086,3311821086,3311821086...
Or even make a data frame directly like this:
Letters Counts1 Counts2 Counts3 ...
0 A 949038913 949038913 949038913 ...
1 C 154135114 154135114 154135114 ...
.
.
.
I tried to use pandas, but I only concatenate them one over the other like this:
Letters Counts
0 A 949038913
1 C 154135114
2 D 602309784
3 E 672070230
4 F 430604264
5 G 760092523
6 H 242152981
7 I 608218717
8 K 558412515
9 L 1057894498
10 N 455966669
11 M 238551663
12 P 554657856
13 Q 423767129
14 R 650581191
15 S 819127381
16 T 632469374
17 V 717790671
18 W 144439568
19 Y 324996779
20 A 5601093669
21 C 714840722
22 D 3311821086
23 E 3714631762
24 F 2359322409
25 G 4449445373
26 H 1321142307
27 I 3403144346
28 K 2941319082
29 L 5982421765
30 M 1431041943
31 N 2289666237
the code was like this:
extension = 'csv'
all_filenames = [i for i in glob.glob('*.{}'.format(extension))]
df_from_each_file = [pd.read_csv(f, header=None, names=['Latters', 'Counts'])
for f in all_filenames]
frame = pd.concat(df_from_each_file, axis=0, ignore_index=True)
Any tip or improvement would be very welcome!
Thank you by your time!
Paulo
use axis=1 in pd.concat function you can refer https://pandas.pydata.org/pandas-docs/stable/user_guide/merging.html