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import pandas as pd
import numpy as np

Concatenation

# NumPy Concatenation
x = [1,2,3]
y = [11,12,13]
z= [111,112,113]
np.concatenate([x,y,z])
array([  1,   2,   3,  11,  12,  13, 111, 112, 113])
# Pandas Series Concatenation similar to np.concatenate
s1 = pd.Series(['A', 'B', 'C'], index=[1, 2, 3])
s2 = pd.Series(['D', 'E', 'F'], index=[4, 5, 6])
pd.concat([s1,s2])
1    A
2    B
3    C
4    D
5    E
6    F
dtype: object
# Pandas DataFrame Concatenantion 
df1 = pd.DataFrame([['a1','b1'],['a2','b2']], index=[1,2], columns=['A','B'])
df2 = pd.DataFrame([['a3','b3'],['a4','b4']], index=[1,2], columns=['A','B'])
print('df1:\n',df1)
print('df2:\n',df2)
print('Concatenate df1 & df2:\n',pd.concat([df1, df2]))
df1: A B 1 a1 b1 2 a2 b2 df2: A B 1 a3 b3 2 a4 b4 Concatenate df1 & df2: A B 1 a1 b1 2 a2 b2 1 a3 b3 2 a4 b4