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This article will explain in detail how to use numpy,pandas,matplotlib for you. The editor thinks it is very practical, so I share it with you as a reference. I hope you can get something after reading this article.

Using the three libraries in Python, you can gracefully analyze the data and get a wild Matlab, which are numpy,pandas and matplotlib.

Numpy is the basic package of high-performance scientific computing and data analysis. Its array multi-dimensional array has rich data types, which can effectively replace loops based on vectorization technology, and the code is simple and fast.

The data frame dataframe in pandas based on numpy integrates all kinds of data analysis tools, which can carry out complex calculation like array array, manipulate data like excel and manipulate data like SQL.

Matplotlib further realizes the drawing function in matlab style. Its powerful data visualization ability can make your data analysis results attractive.

1. Numpy library

Numpy provides three commonly used objects, array array, matrix matrix, and ufunc (universal function).

1, create array

2. Access the array element

3Query array operation

4, use matrix operation

5, use the ufunc object

2. Pandas library

DataFrame in pandas is the most widely used data structure for interactivity in data analysis.

The data structures commonly used in pandas are:

(1) Series: one-dimensional array, similar to one-dimensional array in Numpy.

Only the same data type can be stored in Series.

(2) DataFrame: two-dimensional tabular data structure.

You can think of DataFrame as a container for Series.

(3) Panel: a three-dimensional array that can be understood as a container for DataFrame.

1refine Series object

2, create a DataFrame object

3. Read the DataFrame object from excel

4, add rows

5, delete rows

6, add columns

7, delete column

8, move the column

9, sort

10, splicing

11, select data

There are three ways to select data: subscript index, label index, and Boolean index.

12, export to csv file or excel file

13, commonly used statistical functions

14, time format

Third, matplotlib library

Matplotlib supports functional drawing and object-oriented drawing.

The functional drawing method is consistent with the matlab style, first drawing the image with a sentence, and then decorating it with a series of functions. The object-oriented drawing method is generally completed from top to bottom, first creating figure, then creating subgraph ax, then drawing data, and finally designing various auxiliary elements (including xaxis, yaxis, title, grid,legend, annotate, etc.).

1, line chart

2, bar chart

3, columnar distribution

4, scatter plot

5, pie chart

6. Draw a subgraph

Common shortcut keys for Appendix:Jupyter Notebook

Tab object completion

Shift + Tab object hint help

Ctrl + Enter runs the current cell

Shift + Enter runs the current cell and selects the next cell

Alt + Enter runs the current cell and creates an empty cell below

Esc * M switches to markdown input state

Esc * An insert cell above

Esc * B insert cell below

This is the end of the article on "how to use numpy,pandas,matplotlib". I hope the above content can be of some help to you, so that you can learn more knowledge. if you think the article is good, please share it for more people to see.

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