怎么使用spyder的帮助

在使用Spyder时，有可能要查询某个函数或者某个模块的具体用法。

1、要查看模块的作用说明、简介，可以直接在交互区直接输入：

print(模块名.__doc__)

例如：要查看pandas的介绍

In[1]:print(pd.__doc__)
pandas-apowerfuldataanalysisandmanipulationlibraryforPython
=====================================================================
**pandas**isaPythonpackageprovidingfast,flexible,andexpressivedata
structuresdesignedtomakeworkingwith"relational"or"labeled"databoth
easyandintuitive.Itaimstobethefundamentalhigh-levelbuildingblockfor
doingpractical,**realworld**dataanalysisinPython.Additionally,ithas
thebroadergoalofbecoming**themostpowerfulandflexibleopensourcedata
analysis/manipulationtoolavailableinanylanguage**.Itisalreadywellon
itswaytowardthisgoal.
MainFeatures
-------------
Herearejustafewofthethingsthatpandasdoeswell:
-Easyhandlingofmissingdatainfloatingpointaswellasnon-floating
pointdata
-Sizemutability:columnscanbeinsertedanddeletedfromDataFrameand
higherdimensionalobjects
-Automaticandexplicitdataalignment:objectscanbeexplicitlyaligned
toasetoflabels,ortheusercansimplyignorethelabelsandlet
`Series`,`DataFrame`,etc.automaticallyalignthedataforyouin
computations
-Powerful,flexiblegroupbyfunctionalitytoperformsplit-apply-combine
operationsondatasets,forbothaggregatingandtransformingdata
-Makeiteasytoconvertragged,differently-indexeddatainotherPython
andNumPydatastructuresintoDataFrameobjects
-Intelligentlabel-basedslicing,fancyindexing,andsubsettingoflarge
datasets
-Intuitivemergingandjoiningdatasets
-Flexiblereshapingandpivotingofdatasets
-Hierarchicallabelingofaxes(possibletohavemultiplelabelspertick)
-RobustIOtoolsforloadingdatafromflatfiles(CSVanddelimited),
Excelfiles,databases,andsaving/loadingdatafromtheultrafastHDF5
format
-Timeseries-specificfunctionality:daterangegenerationandfrequency
conversion,movingwindowstatistics,movingwindowlinearregressions,
dateshiftingandlagging,etc.

2、想知道某个函数的用法可以使用：

help(函数名)

例如：要查询pandas的fillna的使用方法

In[2]:help(x.fillna)
Helponmethodfillnainmodulepandas.core.frame:
fillna(value=None,method=None,axis=None,inplace=False,limit=None,downcast=None,**kwargs)methodofpandas.
core.frame.DataFrameinstance
FillNA/NaNvaluesusingthespecifiedmethod
Parameters
----------
value:scalar,dict,Series,orDataFrame
Valuetousetofillholes(e.g.0),alternatelya
dict/Series/DataFrameofvaluesspecifyingwhichvaluetousefor
eachindex(foraSeries)orcolumn(foraDataFrame).(valuesnot
inthedict/Series/DataFramewillnotbefilled).Thisvaluecannot
bealist.
method:{'backfill','bfill','pad','ffill',None},defaultNone
MethodtouseforfillingholesinreindexedSeries
pad/ffill:propagatelastvalidobservationforwardtonextvalid
backfill/bfill:useNEXTvalidobservationtofillgap
axis:{0or'index',1or'columns'}
inplace:boolean,defaultFalse
IfTrue,fillinplace.Note:thiswillmodifyany
otherviewsonthisobject,(e.g.ano-copysliceforacolumnina
DataFrame).
limit:int,defaultNone
Ifmethodisspecified,thisisthemaximumnumberofconsecutive
NaNvaluestoforward/backwardfill.Inotherwords,ifthereis
agapwithmorethanthisnumberofconsecutiveNaNs,itwillonly
bepartiallyfilled.Ifmethodisnotspecified,thisisthe
maximumnumberofentriesalongtheentireaxiswhereNaNswillbe
filled.Mustbegreaterthan0ifnotNone.
downcast:dict,defaultisNone
adictofitem->dtypeofwhattodowncastifpossible,
orthestring'infer'whichwilltrytodowncasttoanappropriate
equaltype(e.g.float64toint64ifpossible)
SeeAlso
--------
reindex,asfreq
Returns
-------
filled:DataFrame