如何在一个文件python中合并多个数据帧

Question

In my code i have received result like this one:

A B C
1 1 1
A B C
2 2 2
A B C
3 3 3

I need to merge those columns (dataframes) to one big dataframe like

 A B C
 1 1 1
 2 2 2
 3 3 3

To merge dataframes from different files its ease like pd.merge(df1,df2) but how to do it when dataframes are in one file? Thanks in advice!

EDIT: to receive my data i converted the lines in my dataset to get dataframes, and i have received in one output each dataset for each line. my code:

def coordinates():
    with open('file.txt') as file:
        for lines in file:
            lines =StringIO(lines[35:61]) #i need only those fields in each line
            abc=pd.read_csv(lines,sep=' ',header=None)
            abc.columns=['A', 'B', 'C','D','E','F']
            print abc

coordinates()

EDIT2: Proposition from s_vishnu its only good for prapared file with same multiple headers. But in my case i have multiple DataFrames generated to the file and each line after header have 0 value. It's many dataframes and each have only one line.

EDIT3: in my file.txt i have big amount of lines with about 80 letters in line like this:

AAA SS SSDAS ASDJAI A 234 33 43 234 2342999 2.31 22 33 SSS SD W2UUQ Q231WQ A 222 11 23 123 1231299 2.31 22 11

and from those line i need only part of information so thats why i did lines =StringIO(lines[35:61]) to take this info. In this example i will need letters [30:55] and create dataframe with them with columns=['A', 'B', 'C','D','E','F'] with sep=' '

Answer 1

my_test.csv :

A, B, C
1, 1 ,1
A, B, C
2, 2, 2
A, B, C
3, 3, 3

Use list slicing .

import pandas as pd
df = pd.read_csv("my_test.csv")
df=df[::2]
print(df)

output:

   A    B   C
0  1   1    1
2  2    2   2
4  3    3   3

df=df[::2] This is advanced list slicing. Where in df[::2] the 2 means starting from 0 increment by 2 step.

But note the index values. They too are in steps of 2. ie 0,2,4,.. to change the index just do this.

import pandas as pd
df = pd.read_csv("my_test.csv")
df=df[::2]

df.index = range(len(df['A']))
print(df)

output:

   A    B   C
0  1   1    1
1  2    2   2
2  3    3   3

So you get the values you desire.

Answer 2

I have found the solution, I've changed the code at the beginning and that was helpfull:

def coordinates():
abc=open('file.txt')
lines=abc.readlines()
        for line in lines:
        abc2=line[20:-7] #i just cut the lines from the begining and from the end, and i dont need to take data from the middle
        abc3=abc2.split()
        pd.DataFrame(abc3) 
        print abc3

coordinates()