Shulou(Shulou.com)06/03 Report--

This article is to share with you what are the three major questions that need to be answered in Python data analysis. The editor thinks it is very practical, so I share it with you to learn. I hope you can get something after reading this article.

The Windows system does not have its own Python tools, so we need to build our own environment. For rookies, we recommend that you install Anaconda, an open source Python distribution, which is easy to install and use, and comes with a large number of toolkits, which is really sweet.

Many cuties do not follow the requirements when building the environment, resulting in a lot of problems have to spend more time and energy to solve, very inconvenient. Two points are emphasized here:

1) Select C disk for installation path!

2) check both advanced options as shown in the figure.

In addition, although the Mac system comes with Python tools, it is also recommended to use an Anaconda for beginners of the Mac system, which will be much more convenient.

Response to error in reading data report

First save the EXCEL file as a CSV file, and then call the pandas toolkit to read it.

Import numpy as np

Import pandas as pd

Import matplotlib.pyplot as plt

# numpy: scientific Computing Toolkit

# pandas: data Analysis Toolkit

# malplotlib: charting toolkit

# improt statement: load the toolkit

Data = pd.read_csv ("path\ database of Party committee secretaries at prefectural and municipal level (2000-10) .csv", encoding = "gbk", engine = 'python')

Print (data)

For error reports when reading data, refer to the following solution:

1) check that all codes are in English, especially punctuation!

# check each comma, single and double quotation marks, parentheses

2) when excel is converted to csv, you can set the encoding to UTF-8 and change the parameters.

Encoding = 'utf-8'

3) when the mac system exports csv, you can change the parameters

Encoding = "gb18030"

4) the file name can be changed to English file name, such as "data.csv"

Data.csv

5) set engine='python'

Engine = 'python'

6) when the amount of data is small, you can also use read_excel, and the code is

Data=pd.read_excel ('path .xlsx')

The premise is that the data is placed in the first sheet; and if it is the second sheet, the code changes to

Data=pd.read_excel ('path .xlsx', sheet_name=1)

* read the sheet_name number from 0, where 1 represents the second sheet

Matplotlib Chinese garbled code

It is also a common and big problem ~ here we take the win10 system and python3.6 version as an example to explain the steps to solve the problem:

* partial excerpt from the original answer https://www.zhihu.com/question/25404709/answer/128171562

Thanks to this bosom friend: si Yi

1) locate matplotlib configuration file:

Import matplotlib

Print (matplotlib.matplotlib_fname ())

# the output of the example is as follows:

# D:\ Program Files\ Python36\ Lib\ site-packages\ matplotlib\ mpl-data

2) the editor opens this file matplotlibrc

Delete the # before the lines font.family and font.sans-serif, and add the Microsoft yahn font Microsoft YaHei after font.sans-serif

3) download fonts: msyh.ttf (Microsoft Acer) is placed under the matplotlib font folder:

# D:\ Program Files\ Python36\ Lib\ site-packages\ matplotlib\ mpl-data\ fonts\ ttf

4) Delete two cached font files in .matplotlib / cache

C:\ Users\ your user name\ .matplotlib

5) restart Python

These are the three major questions that need to be answered in Python data analysis. The editor believes that there are some knowledge points that we may see or use in our daily work. I hope you can learn more from this article. For more details, please follow the industry information channel.

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