# 6.10. Numpy Pandas quiz¶

```import pandas as pd
import numpy as np
```

For the duration of this quiz, assume that pandas has been imported as `pd` and numpy as `np`, as in the cell above.

```names2000 = pd.read_csv('names/yob2000.txt',names=['name','sex','births'])
```

Next assume that `names2000` is the result of the above read command.

## 6.10.1. Selecting columns and rows¶

In the next cell, write down what type of Python object `names2000` is after the cell above has been executed:

```:
```

In the next cell, write an expression selecting the `sex` column of `names2000`:

```:
```

In the next cell wrte an expression that retrieves the fourth through the sixth row of the `birth` column of `names2000` (keeping in mind that the second row is indexed 1):

```:
```

## 6.10.2. Selecting multiple columns¶

What if we just want to know the names and the birth counts, but not the gender? Pandas makes it really easy to select a subset of the columns. Write an expression that returns the subtable of the `names2000` dataframe that contains just the `names` and the `births` columns:

```:
```

When you executed the expression that showed you the subtable, it just showed you a summary. Write an expression that just returns the first 18 rows of the subtable:

```:
```

## 6.10.3. Numpy¶

Assume the following code has been executed:

```import numpy as np
x = np.array([4,3,1,0])
y =np.arange(5)
z = 2 * x
```

Write expressions in the next cell to retrieve 0 from `x`, 4 from `y`, and 6 from `z`:

```:
```

In the next cell, write an expression that generates a 3 by 4 array filled with zeros, and another that generates a 3 by 1 array filled with ones:

```:
```

In the next cell, write an expression that uses an assignment to a splice to make all the even values in `a` be 1. Attention: This can be done more easily in numpy than it can in normal Python. See if you can do it the easy way:

```[ ]: a = np.arange(1,5)
:
```

In the next cell write an expression that produces an array containing result of adding 3 to each of the first 5 integers (1 - 5). There’s a hard way to do this and an easy way. The easy way uses elementwise operations:

```:
```