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Python converts comma to pandas dataframe list

I am trying to convert a comma separated list to a data frame with multiple columns (7).

print (type(mylist)) <type 'list'> Print(mylist) ['AN,2__AAS000,26,20150826113000,-283.000,20150826120000,-283.000', 'AN,2__AE000,26,20150826113000,0.000,20150826120000,0.000',.........

Next, a frame of one column is created:

 df = pd.DataFrame(mylist)

I reviewed the csv built-in functions for Pandas, however my csv data is stored in a list. How can I just hide the list in a frame frame of 7 columns.

Thanks in advance.

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1 answer

You need to split each line in your list:

 import pandas as pd df = pd.DataFrame([sub.split(",") for sub in l]) print(df)

Output:

  0 1 2 3 4 5 6 0 AN 2__AS000 26 20150826113000 -283.000 20150826120000 -283.000 1 AN 2__A000 26 20150826113000 0.000 20150826120000 0.000 2 AN 2__AE000 26 20150826113000 -269.000 20150826120000 -269.000 3 AN 2__AE000 26 20150826113000 -255.000 20150826120000 -255.000 4 AN 2__AE00 26 20150826113000 -254.000 20150826120000 -254.000

If you know how many lines to skip in your csv, you can do it all with read_csv using skiprows=lines_of_metadata :

 import pandas as pd df = pd.read_csv("in.csv",skiprows=3,header=None) print(df)

Or, if each line of metadata starts with a specific character, you can use a comment:

 df = pd.read_csv("in.csv",header=None,comment="#")

If you need to specify more than one character, you can itertools.takewhile , which will discard lines starting with xxx :

 import pandas as pd from itertools import dropwhile import csv with open("in.csv") as f: f = dropwhile(lambda x: x.startswith("#!!"), f) r = csv.reader(f) df = pd.DataFrame().from_records(r)

Using your input, adding some lines starting with C # !!:

 #!! various #!! metadata #!! lines AN,2__AS000,26,20150826113000,-283.000,20150826120000,-283.000 AN,2__A000,26,20150826113000,0.000,20150826120000,0.000 AN,2__AE000,26,20150826113000,-269.000,20150826120000,-269.000 AN,2__AE000,26,20150826113000,-255.000,20150826120000,-255.000 AN,2__AE00,26,20150826113000,-254.000,20150826120000,-254.000

Outputs:

  0 1 2 3 4 5 6 0 AN 2__AS000 26 20150826113000 -283.000 20150826120000 -283.000 1 AN 2__A000 26 20150826113000 0.000 20150826120000 0.000 2 AN 2__AE000 26 20150826113000 -269.000 20150826120000 -269.000 3 AN 2__AE000 26 20150826113000 -255.000 20150826120000 -255.000 4 AN 2__AE00 26 20150826113000 -254.000 20150826120000 -254.000
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