﻿ Pandas: Create a DataFrame from a Numpy array and specify the index column and column headers - w3resource

# Pandas: Create a DataFrame from a Numpy array and specify the index column and column headers

## Pandas: DataFrame Exercise-44 with Solution

Write a Pandas program to create a DataFrame from a Numpy array and specify the index column and column headers.

Sample Solution :

Python Code :

``````import pandas
import numpy
dtype = [('Column1','int32'), ('Column2','float32'), ('Column3','float32')]
values = numpy.zeros(15, dtype=dtype)
index = ['Index'+str(i) for i in range(1, len(values)+1)]
df = pandas.DataFrame(values, index=index)
print(df)
``````

Sample Output:

```          Column1  Column2  Column3
Index1         0      0.0      0.0
Index2         0      0.0      0.0
Index3         0      0.0      0.0
Index4         0      0.0      0.0
Index5         0      0.0      0.0
Index6         0      0.0      0.0
Index7         0      0.0      0.0
Index8         0      0.0      0.0
Index9         0      0.0      0.0
Index10        0      0.0      0.0
Index11        0      0.0      0.0
Index12        0      0.0      0.0
Index13        0      0.0      0.0
Index14        0      0.0      0.0
Index15        0      0.0      0.0
```

Python-Pandas Code Editor:

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## Python: Tips of the Day

Inserting if statements using conditional list comprehensions:

```x = [1, 2, 3, 4, 5, 6]
result = []
for idx in range(len(x)):
if x[idx] % 2 == 0:
result.append(x[idx] * 2)
else:
result.append(x[idx])
result
```

Output:

```[1, 4, 3, 8, 5, 12]
```
`[(element * 2 if element % 2 == 0 else element) for element in x]`

Output:

```[1, 4, 3, 8, 5, 12]
```
`[element * 2 for element in x if element % 2 == 0]`

Output:

```[4, 8, 12]
```