Course Content

Advanced Techniques in pandas

## Advanced Techniques in pandas

# Getting Familiar With lambda Functions

Sometimes we need to put some conditions on the indices. In these cases, you need to use a `lambda`

function inside `iloc[]`

.

Let's figure out what we can do using `lambda`

:

This code will output the first five rows of the dataset, the rows with the indices `0`

, `1`

, `2`

, `3`

, and `4`

.

`lambda x`

-`x`

is the argument we will work with (the item of the data set);`x.index`

- extracts only values of rows' indices;`x.index < 5`

- the condition according to which we will extract data. Here, only rows with indices that are less than`5`

.

Task

Your task here is to divide data into two groups: one has odd indices and the other even. Follow the algorithm:

- Import the
`pandas`

library with the`pd`

alias. - Read the
**csv**file. - Extract only rows with even indices:
- Apply the
`.iloc[]`

attribute to the`data`

; - Within the
`.iloc[]`

attribute, apply the`lambda`

function with the`x`

argument; - Set a condition to check if the number is even (if you do not know how to do this, check the hint).

- Apply the
- Extract only rows with odd indices:
- Apply the
`.iloc[]`

attribute to the`data`

; - Within the
`.iloc[]`

attribute, apply the`lambda`

function with the`x`

argument; - Set a condition to check if the number is odd (if you do not know how to do this, check the hint).

- Apply the
- Output data:
- Output
**the first five**rows of the`even`

indices; - Output
**the last five**rows of the`odd`

indices.

- Output

Thanks for your feedback!

# Getting Familiar With lambda Functions

Sometimes we need to put some conditions on the indices. In these cases, you need to use a `lambda`

function inside `iloc[]`

.

Let's figure out what we can do using `lambda`

:

This code will output the first five rows of the dataset, the rows with the indices `0`

, `1`

, `2`

, `3`

, and `4`

.

`lambda x`

-`x`

is the argument we will work with (the item of the data set);`x.index`

- extracts only values of rows' indices;`x.index < 5`

- the condition according to which we will extract data. Here, only rows with indices that are less than`5`

.

Task

Your task here is to divide data into two groups: one has odd indices and the other even. Follow the algorithm:

- Import the
`pandas`

library with the`pd`

alias. - Read the
**csv**file. - Extract only rows with even indices:
- Apply the
`.iloc[]`

attribute to the`data`

; - Within the
`.iloc[]`

attribute, apply the`lambda`

function with the`x`

argument; - Set a condition to check if the number is even (if you do not know how to do this, check the hint).

- Apply the
- Extract only rows with odd indices:
- Apply the
`.iloc[]`

attribute to the`data`

; - Within the
`.iloc[]`

attribute, apply the`lambda`

function with the`x`

argument; - Set a condition to check if the number is odd (if you do not know how to do this, check the hint).

- Apply the
- Output data:
- Output
**the first five**rows of the`even`

indices; - Output
**the last five**rows of the`odd`

indices.

- Output

Thanks for your feedback!

# Getting Familiar With lambda Functions

Sometimes we need to put some conditions on the indices. In these cases, you need to use a `lambda`

function inside `iloc[]`

.

Let's figure out what we can do using `lambda`

:

This code will output the first five rows of the dataset, the rows with the indices `0`

, `1`

, `2`

, `3`

, and `4`

.

`lambda x`

-`x`

is the argument we will work with (the item of the data set);`x.index`

- extracts only values of rows' indices;`x.index < 5`

- the condition according to which we will extract data. Here, only rows with indices that are less than`5`

.

Task

Your task here is to divide data into two groups: one has odd indices and the other even. Follow the algorithm:

- Import the
`pandas`

library with the`pd`

alias. - Read the
**csv**file. - Extract only rows with even indices:
- Apply the
`.iloc[]`

attribute to the`data`

; - Within the
`.iloc[]`

attribute, apply the`lambda`

function with the`x`

argument; - Set a condition to check if the number is even (if you do not know how to do this, check the hint).

- Apply the
- Extract only rows with odd indices:
- Apply the
`.iloc[]`

attribute to the`data`

; - Within the
`.iloc[]`

attribute, apply the`lambda`

function with the`x`

argument; - Set a condition to check if the number is odd (if you do not know how to do this, check the hint).

- Apply the
- Output data:
- Output
**the first five**rows of the`even`

indices; - Output
**the last five**rows of the`odd`

indices.

- Output

Thanks for your feedback!

`lambda`

function inside `iloc[]`

.

Let's figure out what we can do using `lambda`

:

`0`

, `1`

, `2`

, `3`

, and `4`

.

`lambda x`

-`x`

is the argument we will work with (the item of the data set);`x.index`

- extracts only values of rows' indices;`x.index < 5`

- the condition according to which we will extract data. Here, only rows with indices that are less than`5`

.

Task

- Import the
`pandas`

library with the`pd`

alias. - Read the
**csv**file. - Extract only rows with even indices:
- Apply the
`.iloc[]`

attribute to the`data`

; - Within the
`.iloc[]`

attribute, apply the`lambda`

function with the`x`

argument; - Set a condition to check if the number is even (if you do not know how to do this, check the hint).

- Apply the
- Extract only rows with odd indices:
- Apply the
`.iloc[]`

attribute to the`data`

; - Within the
`.iloc[]`

attribute, apply the`lambda`

function with the`x`

argument; - Set a condition to check if the number is odd (if you do not know how to do this, check the hint).

- Apply the
- Output data:
- Output
**the first five**rows of the`even`

indices; - Output
**the last five**rows of the`odd`

indices.

- Output