Một thẻ đã tồn tại với tên chi nhánh được cung cấp. Nhiều lệnh GIT chấp nhận cả tên thẻ và tên chi nhánh, vì vậy việc tạo nhánh này có thể gây ra hành vi bất ngờ. Bạn có chắc là bạn muốn tạo chi nhánh này?
Một thẻ đã tồn tại với tên chi nhánh được cung cấp. Nhiều lệnh GIT chấp nhận cả tên thẻ và tên chi nhánh, vì vậy việc tạo nhánh này có thể gây ra hành vi bất ngờ. Bạn có chắc là bạn muốn tạo chi nhánh này?
2. Giao diện Python
//campus.datacamp.com/courses/intro-to-python-for-data-science/chapter-1-python-basics?ex=2
In the Python script on the right, you can type Python code to solve the exercises. If you hit Submit Answer, your python script [script.py] is executed and the output is shown in the IPython Shell. DataCamp checks whether your submission is correct and gives you feedback.
You can hit Submit Answer as often as you want. If you're stuck, you can click Get Hint, and ultimately Get Solution.
You can also use the IPython Shell interactively by simply typing commands and hitting Enter. When you work in the shell directly, your code will not be checked for correctness so it is a great way to experiment.
Hướng dẫn
Experiment in the IPython Shell; type 5 / 8, for example.
Add another line of code to the Python script: print[7 + 10].
Hit Submit Answer to execute the Python script and receive feedback.
In [1]:
# Example, do not modify!
print[5 / 8]
# Put code below here
print[7 + 10]
0.625
17
//campus.datacamp.com/courses/intro-to-python-for-data-science/chapter-1-python-basics?ex=4
Something that Filip didn't mention in his videos is that you can add comments to your Python scripts. Comments are important to make sure that you and others can understand what your code is about.
To add comments to your Python script, you can use the # tag. These comments are not run as Python code, so they will not influence your result. As an example, take the comment on the right, # Just testing division: it is completely ignored during execution.
Hướng dẫn
Above the print[7 + 10], add the comment # Addition works too.
In [2]:
# Just testing division
print[5 / 8]
# Addition works too
print[7 + 10]
0.625
17
Bạn có muốn tạo khóa học của riêng bạn không? Sử dụng Datacamp Dạy, bạn có thể dễ dàng tạo và lưu trữ hướng dẫn tương tác của riêng bạn miễn phí. Sử dụng cùng một hệ thống Datacamp Course Creaters sử dụng để phát triển các khóa học của họ và chia sẻ kiến thức Python của bạn với phần còn lại của thế giới.
//campus.datacamp.com/courses/intro-to-python-for-data-science/chapter-1-python-basics?ex=5
Python is perfectly suited to do basic calculations. Apart from addition, subtraction, multiplication and division, there is also support for more advanced operations such as:
Exponentiation: **. This operator raises the number to its left to the power of the number to its right: for example 4**2 will give 16.
Modulo: %. It returns the remainder of the division of the number to the left by the number on its right, for example 18 % 7 equals 4.
The code in the script on the right gives some examples.
Hướng dẫn
Suppose you have $100, which you can invest with a 10% return each year. After one year, it's 100×1.1=110 dollars, and after two years it's 100×1.1×1.1=121. Add code on the right to calculate how much money you end up with after 7 years.
Experiment in the IPython Shell; type 5 / 8, for example.
Add another line of code to the Python script: print[7 + 10].
Hit Submit Answer to execute the Python script and receive feedback.
0Experiment in the IPython Shell; type 5 / 8, for example.
Add another line of code to the Python script: print[7 + 10].
Hit Submit Answer to execute the Python script and receive feedback.
1Experiment in the IPython Shell; type 5 / 8, for example.
Add another line of code to the Python script: print[7 + 10].
Hit Submit Answer to execute the Python script and receive feedback.
2Experiment in the IPython Shell; type 5 / 8, for example.
Add another line of code to the Python script: print[7 + 10].
Hit Submit Answer to execute the Python script and receive feedback.
3Experiment in the IPython Shell; type 5 / 8, for example.
Add another line of code to the Python script: print[7 + 10].
Hit Submit Answer to execute the Python script and receive feedback.
4Experiment in the IPython Shell; type 5 / 8, for example.
Add another line of code to the Python script: print[7 + 10].
Hit Submit Answer to execute the Python script and receive feedback.
5Experiment in the IPython Shell; type 5 / 8, for example.
Add another line of code to the Python script: print[7 + 10].
Hit Submit Answer to execute the Python script and receive feedback.
6Experiment in the IPython Shell; type 5 / 8, for example.
Add another line of code to the Python script: print[7 + 10].
Hit Submit Answer to execute the Python script and receive feedback.
7Experiment in the IPython Shell; type 5 / 8, for example.
Add another line of code to the Python script: print[7 + 10].
Hit Submit Answer to execute the Python script and receive feedback.
8Experiment in the IPython Shell; type 5 / 8, for example.
Add another line of code to the Python script: print[7 + 10].
Hit Submit Answer to execute the Python script and receive feedback.
9
In [1]:
# Example, do not modify!
print[5 / 8]
# Put code below here
print[7 + 10]
0
In [1]:
# Example, do not modify!
print[5 / 8]
# Put code below here
print[7 + 10]
1
In [1]:
# Example, do not modify!
print[5 / 8]
# Put code below here
print[7 + 10]
2
In [1]:
# Example, do not modify!
print[5 / 8]
# Put code below here
print[7 + 10]
3
In [1]:
# Example, do not modify!
print[5 / 8]
# Put code below here
print[7 + 10]
4
In [1]:
# Example, do not modify!
print[5 / 8]
# Put code below here
print[7 + 10]
5
In [1]:
# Example, do not modify!
print[5 / 8]
# Put code below here
print[7 + 10]
6
In [1]:
# Example, do not modify!
print[5 / 8]
# Put code below here
print[7 + 10]
7
In [1]:
# Example, do not modify!
print[5 / 8]
# Put code below here
print[7 + 10]
8
In [1]:
# Example, do not modify!
print[5 / 8]
# Put code below here
print[7 + 10]
9
0.625
17
0
0.625
17
1
0.625
17
2
0.625
17
3Bạn có muốn tạo khóa học của riêng bạn không? Sử dụng Datacamp Dạy, bạn có thể dễ dàng tạo và lưu trữ hướng dẫn tương tác của riêng bạn miễn phí. Sử dụng cùng một hệ thống Datacamp Course Creaters sử dụng để phát triển các khóa học của họ và chia sẻ kiến thức Python của bạn với phần còn lại của thế giới.
//campus.datacamp.com/courses/intro-to-python-for-data-science/chapter-1-python-basics?ex=7
0.625
17
4Hướng dẫn
0.625
17
5
0.625
17
6
0.625
17
7Bạn có muốn tạo khóa học của riêng bạn không? Sử dụng Datacamp Dạy, bạn có thể dễ dàng tạo và lưu trữ hướng dẫn tương tác của riêng bạn miễn phí. Sử dụng cùng một hệ thống Datacamp Course Creaters sử dụng để phát triển các khóa học của họ và chia sẻ kiến thức Python của bạn với phần còn lại của thế giới.
//campus.datacamp.com/courses/intro-to-python-for-data-science/chapter-1-python-basics?ex=8
0.625
17
8Hướng dẫn
0.625
17
9
Something that Filip didn't mention in his videos is that you can add comments to your Python scripts. Comments are important to make sure that you and others can understand what your code is about.
To add comments to your Python script, you can use the # tag. These comments are not run as Python code, so they will not influence your result. As an example, take the comment on the right, # Just testing division: it is completely ignored during execution.
0Something that Filip didn't mention in his videos is that you can add comments to your Python scripts. Comments are important to make sure that you and others can understand what your code is about.
To add comments to your Python script, you can use the # tag. These comments are not run as Python code, so they will not influence your result. As an example, take the comment on the right, # Just testing division: it is completely ignored during execution.
19. Các loại biến khác
//campus.datacamp.com/courses/intro-to-python-for-data-science/chapter-1-python-basics?ex=9
Something that Filip didn't mention in his videos is that you can add comments to your Python scripts. Comments are important to make sure that you and others can understand what your code is about.
To add comments to your Python script, you can use the # tag. These comments are not run as Python code, so they will not influence your result. As an example, take the comment on the right, # Just testing division: it is completely ignored during execution.
2Hướng dẫn
Something that Filip didn't mention in his videos is that you can add comments to your Python scripts. Comments are important to make sure that you and others can understand what your code is about.
To add comments to your Python script, you can use the # tag. These comments are not run as Python code, so they will not influence your result. As an example, take the comment on the right, # Just testing division: it is completely ignored during execution.
3Something that Filip didn't mention in his videos is that you can add comments to your Python scripts. Comments are important to make sure that you and others can understand what your code is about.
To add comments to your Python script, you can use the # tag. These comments are not run as Python code, so they will not influence your result. As an example, take the comment on the right, # Just testing division: it is completely ignored during execution.
410. đoán loại
//campus.datacamp.com/courses/intro-to-python-for-data-science/chapter-1-python-basics?ex=10
Something that Filip didn't mention in his videos is that you can add comments to your Python scripts. Comments are important to make sure that you and others can understand what your code is about.
To add comments to your Python script, you can use the # tag. These comments are not run as Python code, so they will not influence your result. As an example, take the comment on the right, # Just testing division: it is completely ignored during execution.
5Câu trả lời có thể
Something that Filip didn't mention in his videos is that you can add comments to your Python scripts. Comments are important to make sure that you and others can understand what your code is about.
To add comments to your Python script, you can use the # tag. These comments are not run as Python code, so they will not influence your result. As an example, take the comment on the right, # Just testing division: it is completely ignored during execution.
611. Hoạt động với các loại khác
//campus.datacamp.com/courses/intro-to-python-for-data-science/chapter-1-python-basics?ex=11
Something that Filip didn't mention in his videos is that you can add comments to your Python scripts. Comments are important to make sure that you and others can understand what your code is about.
To add comments to your Python script, you can use the # tag. These comments are not run as Python code, so they will not influence your result. As an example, take the comment on the right, # Just testing division: it is completely ignored during execution.
7Hướng dẫn
Something that Filip didn't mention in his videos is that you can add comments to your Python scripts. Comments are important to make sure that you and others can understand what your code is about.
To add comments to your Python script, you can use the # tag. These comments are not run as Python code, so they will not influence your result. As an example, take the comment on the right, # Just testing division: it is completely ignored during execution.
8Something that Filip didn't mention in his videos is that you can add comments to your Python scripts. Comments are important to make sure that you and others can understand what your code is about.
To add comments to your Python script, you can use the # tag. These comments are not run as Python code, so they will not influence your result. As an example, take the comment on the right, # Just testing division: it is completely ignored during execution.
9Above the print[7 + 10], add the comment # Addition works too.
012. Chuyển đổi loại
//campus.datacamp.com/courses/intro-to-python-for-data-science/chapter-1-python-basics?ex=12
Above the print[7 + 10], add the comment # Addition works too.
1Hướng dẫn
Above the print[7 + 10], add the comment # Addition works too.
2Above the print[7 + 10], add the comment # Addition works too.
3Above the print[7 + 10], add the comment # Addition works too.
413. Python có thể xử lý mọi thứ không?
//campus.datacamp.com/courses/intro-to-python-for-data-science/chapter-1-python-basics?ex=13
Above the print[7 + 10], add the comment # Addition works too.
5Câu trả lời có thể
Above the print[7 + 10], add the comment # Addition works too.
6
Khóa học khoa học dữ liệu Datacamp có xứng đáng không?
Nếu bạn hoàn thành một chương hàng ngày trong Datacamp, thì nó sẽ có lợi cho bạn.DataCamp đã trải nghiệm các chuyên gia và họ sẽ giúp bạn học khoa học dữ liệu từ đầu.Vì vậy, tôi sẽ nói các khóa học Datacamp hoàn toàn xứng đáng, đặc biệt nếu bạn là người mới bắt đầu.Datacamp courses are totally worth it, especially if you are a beginner.
Giới thiệu về Python miễn phí trên DataCamp?
Bạn có muốn tạo khóa học của riêng bạn không?Sử dụng Datacamp Dạy, bạn có thể dễ dàng tạo và lưu trữ hướng dẫn tương tác của riêng bạn miễn phí.Sử dụng cùng một hệ thống Datacamp Course Creaters sử dụng để phát triển các khóa học của họ và chia sẻ kiến thức Python của bạn với phần còn lại của thế giới.Using DataCamp Teach, you can easily create and host your own interactive tutorial for free. Use the same system DataCamp course creators use to develop their courses, and share your Python knowledge with the rest of the world.
Nhà khoa học dữ liệu Datacamp có miễn phí Python không?
Truy cập miễn phí vào tất cả các khóa học cả tuần!!
Khóa học DataCamp Python có tốt không?
Vâng, Datacamp là tốt cho việc học Python.Nó cung cấp một trải nghiệm học tập tuyệt vời cho người mới bắt đầu tìm kiếm nội dung học tập về chủ đề này.Các khóa học Datacamp Python là các khóa học giới thiệu giúp người học hiểu các khái niệm chính trong Python.. It provides a superb learning experience for beginners looking to get learning content on the topic. DataCamp Python courses are introductory courses that help learners understand key concepts in Python.