Until now, I have read and concatenated the data with the following code, but can I use the for statement to make the first 10 lines smart?
import numpy as np
import pandas aspd
from pandas import Series, DataFrame
import matplotlib.pyplot asplt
%matplotlib inline
da1 = pd.read_csv("data-1.csv", header = None)#
da2=pd.read_csv("data-2.csv", header=None)#
da3=pd.read_csv("data-3.csv", header=None)#
da4=pd.read_csv("data-4.csv", header=None)#
da5=pd.read_csv("data-5.csv", header=None)#
da6=pd.read_csv("data-6.csv", header=None)#
da7=pd.read_csv("data-7.csv", header=None)#
da8=pd.read_csv("data-8.csv", header=None)#
da9=pd.read_csv("data-9.csv", header=None)#
da10=pd.read_csv("data-10.csv", header=None)#
da_all=pd.concat([da1, da2, da3, da4, da5, da6, da7, da8, da9, da10], Axis=1, sort=False)
plt.plot(ch, da_all [0:12], linestyle='None', marker='o')
np.savetxt("data-all.csv", da_all, delimiter=",")#
An error occurred when I tried using the following code.
# Preprocessing
# Data Integration (for pre-transposition preprocessing)
for n1 in range (1,11):
f"da{n1}" = pd.read_csv(f"201013-945-del-{n1}.csv", header=None)#
da_all=pd.concat([da1, da2, da3, da4, da5, da6, da7, da8, da9, da10], Axis=1, sort=False)
plt.plot(ch, da_all [0:12], linestyle='None', marker='o')
np.savetxt("201013-945-del-all.csv", da_all, delimiter=",")#
I think you've already given your own answers...
da_all=pd.concat(
[pd.read_csv(f"data-{i+1}.csv", header=None) for i in range(10)],
axis=1, sort=False
)
I think the code below is a common code using for loop.
df_list=[]
for i in range (1,11):
df_list.append(pd.read_csv(f"data-{i}.csv", header=None))
df_all=pd.concat(df_list,axis=1,sort=False)
I don't recommend it, but I think the code that the questioner wanted to write is as follows.
for n1 in range (1,11):
exec("da"+str(n1)+"=pd.read_csv(f'data-{n1}.csv', header=None)")
da_all=pd.concat([da1, da2, da3, da4, da5, da6, da7, da8, da9, da10], Axis=1, sort=False)
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