Delete one or more columns of Pandas Dataframe:method One : Direct del df[' Column-name ']method Two : Using the Drop method, there are three types of equivalent expressions:1. df= df.drop (' column_name ', 1);2. Df.drop (' column_name ', Axis=1, Inplace=true)3. Df.drop ([df.columns[[0,1, 3]], axis=1,inplace=true) # Note:zero indexedNote : Usually there is a inplace optional parameter that modifies the original array and returns a new array. If set to
DF1 is the test data for the DATAFRAME structure:The DF1 data is read from the TEST.XLSX document, using the sample code as follows:#-*-Coding:utf-8-*-import Tushare as Tsimport pandas as Pddf = Pd.read_excel (' test.xlsx ') df1 = Df.head (Ten) #dataframe按索引In ascending order, the default is ascending #print df1.sort_index () #
This question mainly writes the method of sorting series and dataframe according to index or value
Code:
#coding =utf-8
Import pandas as PD
import numpy as NP
#以下实现排序功能.
SERIES=PD. Series ([3,4,1,6],index=[' B ', ' A ', ' d ', ' C '])
FRAME=PD. Dataframe ([[2,4,1,5],[3,1,4,5],[5,1,4,2]],columns=[' B ', ' A ', ' d ', ' C '],index=[' one ', ' two ', ' three '])
pr
Tags: Establish connection copy TOC UTF8 identify Data-nec LDB serviceWrites pandas's dataframe data to the MySQL database + sqlalchemy [Python]View PlainCopyprint?
IMPORTNBSP;PANDASNBSP;ASNBSP;PDNBSP;NBSP;
fromsqlalchemyimportcreate_engine
NBSP;NBSP;
# #将数据写入mysql的数据库, However, you need to establish a connection through Sqlalchemy.create_engine, and the character encoding is set to UTF8, otherwise some Latin character
convert to a format that can be found using XPath
= Doc.xpath ('//table ')
find all the tables in the document and return a list
Let's look at the source code of the Web page and find the form that needs to be retrieved
The first behavior title of the table, the following behavior data, we define a function to get them separately:
def _unpack (Row, kind= ' TD '):
ELTs = Row.xpath ('.//%s '%kind)
# Get data based on label type return
[Val.text_content () For Val in ELTs]
# Use
Hierarchical Indexes Hierarchical indexing means you can have multiple indexes on an array, for example: a bit like a merged cell in Excel, right?Select a subset of the data based on the index to select a subset of the data from the other layer:Select data in the same way as the index in the layer:Multi-index series conversion to Dataframe hierarchical indexes play an important role in data reshaping and gr
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