I have 20 csv files with the same basename and a number from 100 to 2000 with an increment of 100 between files, such that samp_100.csv, samp_200.csv, samp_300.csv, ..., samp_1900.csv, samp_2000.csv.
I am trying to read these files into python. I am trying the following.
T = np.arange(100,2100,100)
for i in T:
df = pd.read_csv("samp_{i}.csv".format(i=i))
Although I do not get an error, the files aren't read in the correct order from 100 to 2000. When I use df.head, I do not see the first lines of the file samp_100.csv. Also the files are concatenated into a single file called df. Is there an equivalent way to achieve this but instead have 20 separate dataframes with the names df_100, df_200, ..., df_1900, df_2000?
CodePudding user response:
You need pandas.concat
.
Try this :
import numpy as np
import pandas as pd
T = np.arange(100,2100,100)
list_of_df = []
for i in T:
temp_df = pd.read_csv(f"samp_{i}.csv")
list_of_df.append(temp_df)
df = pd.concat(list_of_df, axis=0, ignore_index=True)
If you need to add a column with the name of the .csv
, include the line below after calling pandas.read_csv
inside the loop.
temp_df.insert(0, "filename", f"samp_{i}")