Зміст курсу
Advanced Techniques in pandas
Advanced Techniques in pandas
Selecting Specific Rows and Columns
Okay, you've dealt with the previous chapters, and now is the right time to combine your knowledge. You can specify both rows and columns; to do so, you just need to be familiar with the .loc[]
attribute.
This function allows us to do plenty of different slicing operations, but for now, we will just consolidate knowledge from the previous chapters.
As usual, look at the example and then at the output.
data.loc[2:5, ['Director', 'ReleaseYear']]
- outputs rows with the indices2
,3
,4
,5
(but remember that the indices start from0
) from the columns'Director'
and'ReleaseYear'
(.loc[]
includes the last index that you put into[]
);data.loc[:5, ['Director', 'ReleaseYear']]
- outputs rows with the indices0
,1
,2
,3
,4
,5
from the columns'Director'
and'ReleaseYear'
;data.loc[997:, ['Director', 'ReleaseYear']]
- outputs rows with the indices997
,998
,999
(999
is the index of the last row) from the columns'Director'
and'ReleaseYear'
;data.loc[:, ['Director', 'ReleaseYear']]
ordata[['Director', 'ReleaseYear']]
- outputs all rows from the columns'Director'
and'ReleaseYear'
.
Завдання
Your task here is to output the necessary rows and columns. Follow the algorithm:
- Import the
pandas
library with thepd
alias. - Read the csv file.
- Assign to
data
variable information about the columns'Title'
,'Stars'
,'Category'
(in this order) with rows with indices from15
to85
. - Output the
data_extracted
variable.
Once you've completed this task, click the button below the code to check your solution.
Дякуємо за ваш відгук!
Selecting Specific Rows and Columns
Okay, you've dealt with the previous chapters, and now is the right time to combine your knowledge. You can specify both rows and columns; to do so, you just need to be familiar with the .loc[]
attribute.
This function allows us to do plenty of different slicing operations, but for now, we will just consolidate knowledge from the previous chapters.
As usual, look at the example and then at the output.
data.loc[2:5, ['Director', 'ReleaseYear']]
- outputs rows with the indices2
,3
,4
,5
(but remember that the indices start from0
) from the columns'Director'
and'ReleaseYear'
(.loc[]
includes the last index that you put into[]
);data.loc[:5, ['Director', 'ReleaseYear']]
- outputs rows with the indices0
,1
,2
,3
,4
,5
from the columns'Director'
and'ReleaseYear'
;data.loc[997:, ['Director', 'ReleaseYear']]
- outputs rows with the indices997
,998
,999
(999
is the index of the last row) from the columns'Director'
and'ReleaseYear'
;data.loc[:, ['Director', 'ReleaseYear']]
ordata[['Director', 'ReleaseYear']]
- outputs all rows from the columns'Director'
and'ReleaseYear'
.
Завдання
Your task here is to output the necessary rows and columns. Follow the algorithm:
- Import the
pandas
library with thepd
alias. - Read the csv file.
- Assign to
data
variable information about the columns'Title'
,'Stars'
,'Category'
(in this order) with rows with indices from15
to85
. - Output the
data_extracted
variable.
Once you've completed this task, click the button below the code to check your solution.
Дякуємо за ваш відгук!
Selecting Specific Rows and Columns
Okay, you've dealt with the previous chapters, and now is the right time to combine your knowledge. You can specify both rows and columns; to do so, you just need to be familiar with the .loc[]
attribute.
This function allows us to do plenty of different slicing operations, but for now, we will just consolidate knowledge from the previous chapters.
As usual, look at the example and then at the output.
data.loc[2:5, ['Director', 'ReleaseYear']]
- outputs rows with the indices2
,3
,4
,5
(but remember that the indices start from0
) from the columns'Director'
and'ReleaseYear'
(.loc[]
includes the last index that you put into[]
);data.loc[:5, ['Director', 'ReleaseYear']]
- outputs rows with the indices0
,1
,2
,3
,4
,5
from the columns'Director'
and'ReleaseYear'
;data.loc[997:, ['Director', 'ReleaseYear']]
- outputs rows with the indices997
,998
,999
(999
is the index of the last row) from the columns'Director'
and'ReleaseYear'
;data.loc[:, ['Director', 'ReleaseYear']]
ordata[['Director', 'ReleaseYear']]
- outputs all rows from the columns'Director'
and'ReleaseYear'
.
Завдання
Your task here is to output the necessary rows and columns. Follow the algorithm:
- Import the
pandas
library with thepd
alias. - Read the csv file.
- Assign to
data
variable information about the columns'Title'
,'Stars'
,'Category'
(in this order) with rows with indices from15
to85
. - Output the
data_extracted
variable.
Once you've completed this task, click the button below the code to check your solution.
Дякуємо за ваш відгук!
Okay, you've dealt with the previous chapters, and now is the right time to combine your knowledge. You can specify both rows and columns; to do so, you just need to be familiar with the .loc[]
attribute.
This function allows us to do plenty of different slicing operations, but for now, we will just consolidate knowledge from the previous chapters.
As usual, look at the example and then at the output.
data.loc[2:5, ['Director', 'ReleaseYear']]
- outputs rows with the indices2
,3
,4
,5
(but remember that the indices start from0
) from the columns'Director'
and'ReleaseYear'
(.loc[]
includes the last index that you put into[]
);data.loc[:5, ['Director', 'ReleaseYear']]
- outputs rows with the indices0
,1
,2
,3
,4
,5
from the columns'Director'
and'ReleaseYear'
;data.loc[997:, ['Director', 'ReleaseYear']]
- outputs rows with the indices997
,998
,999
(999
is the index of the last row) from the columns'Director'
and'ReleaseYear'
;data.loc[:, ['Director', 'ReleaseYear']]
ordata[['Director', 'ReleaseYear']]
- outputs all rows from the columns'Director'
and'ReleaseYear'
.
Завдання
Your task here is to output the necessary rows and columns. Follow the algorithm:
- Import the
pandas
library with thepd
alias. - Read the csv file.
- Assign to
data
variable information about the columns'Title'
,'Stars'
,'Category'
(in this order) with rows with indices from15
to85
. - Output the
data_extracted
variable.
Once you've completed this task, click the button below the code to check your solution.