# How to Combine Multiple Numpy Arrays into a Dataframe

This tutorial will show how you can combine multiple arrays (e.g., 2 arrays of X and Y) into a Pandas dataframe. The following summarizes the two methods.

Method 1:

pd.DataFrame ({‘X’:X,’Y’:Y})

Method 2:

combined_array=np.column_stack((X,Y))
pd.DataFrame(combined_array, columns = [‘X’,’Y’])

## Two Examples of Combining Arrays into Dataframe

### Example for Method 1:

In the following, we create two arrays, X and Y. Then, we combine them into a pandas dataframe.

``````# Import numpy and pandas
import numpy as np
import pandas as pd

# Create two Numpy arrays, X and Y
X = np.array([5, 2, 3, 4, 10, 11, 14])
Y = np.array([3, 1, 2, 5, 14, 15, 16])

# combine two arrays into a dataframe and print it out
df_1 = pd.DataFrame ({'X':X,'Y':Y})
print (df_1)``````

Output:

```    X   Y
0   5   3
1   2   1
2   3   2
3   4   5
4  10  14
5  11  15
6  14  16```

### Example for Method 2:

We can use np.column_stack() to combine two 1-D arrays X and Y into a 2-D array. Then, we can use `pd.DataFrame` to change it into a dataframe.

``````# Import numpy and pandas
import numpy as np
import pandas as pd

# Create two Numpy arrays, X and Y
X = np.array([5, 2, 3, 4, 10, 11, 14])
Y = np.array([3, 1, 2, 5, 14, 15, 16])

# combine two 1-D arrays into a single 2-D array
combined_array=np.column_stack((X,Y))
print("combined array:\n", combined_array)

# combine two arrays into a dataframe and print it out
df_2 = pd.DataFrame(combined_array, columns = ['X','Y'])
print("combined dataframe:\n",df_2)``````

Output:

```combined array:
[[ 5  3]
[ 2  1]
[ 3  2]
[ 4  5]
[10 14]
[11 15]
[14 16]]

combined dataframe:
X   Y
0   5   3
1   2   1
2   3   2
3   4   5
4  10  14
5  11  15
6  14  16```