尝试使用 python 在 Jupyter Notebook 中读取多个.csv 文件时出错

Question

I am given a file that contains 1000.csv files(data0,data1,data2..........,data999) and I need to read all those files. So, I tried it on my own. This was my approach: read data0.csv and perform transpose on it and then loop it through all the data*.csv files and then append them. But I was getting an error. Could someone help me out? Reading data0.csv file and transposing it:

df = pd.read_csv('data0.csv')  
print (df.head(10))
df_temp = df
df_main = df_temp.transpose()
df_main

new_df = [df_main]
for i in range(1000):
filename = "data%d.csv"%i
df_s = pd.read_csv(filename)
new_df= pd.concat([df_s])
new_df[1]

looping through 1000 files, transposing and concating:

after transposing and appending all the 1000 csv files I should be getting 1000 rows x 150 columns. But I am not getting that.

Answer 1

I couldn't test this, because you did not provide an example of your file as text. Please try to provide a minimal reproducible example next time.

My solution is a minor variation of this SO post mentioned by @Ranika Nisal.

dfs = [pd.read_csv(f'data{i}.csv') for i in range(1000)]
df = pd.concat(dfs, axis=0, ignore_index=True)

Your solution did not generate a list of dataframes which is required for pd.concat() to work. Also, you tried to access the second dataframe with new_df[1] but there was only one element in your list. That's the reason why you've received a KeyError .