[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"$f8SMTfW-AgFrTHIZAxbFxJ_Zt0XeGA3CabhjrQriZmdk":3},{"answer":4,"createTime":5,"id":6,"options":7,"origin":12,"question":19,"related":20,"source":31,"type":32},[],"2024-07-04 23:15:46",157382678,[8,9,10,11],"header","encoding","sep","delimiter",{"count":13,"courseId":14,"courseImg":15,"courseName":16,"workId":17,"workName":18},19,"e0a8ff10ba8584fbdd3772c0bcd2f12a","https:\u002F\u002Ftihai-oss-cloud.itihey.com\u002Fimg\u002Fec2c7b23907c0b015fcd6e487b9d695b.png","数据分析与应用","work_35794654","第四章Pandas-选择和填空训练","DataFrame中读取CSV格式的文件时,为了保证中文字符能成功读取,需要配置read_csv命令中的哪个参数",[21,33,42,45,55,64,73,82,91,100],{"answer":22,"createTime":23,"id":24,"options":25,"question":30,"source":31,"type":32},[],"2024-07-04 13:19:02",157382676,[26,27,28,29],"to_csv()","to_txt()","save_txt()","save_csv()","pandas中保存文本文件用到的是( )","v1",0,{"answer":34,"createTime":5,"id":35,"options":36,"question":41,"source":31,"type":32},[],157382677,[37,38,39,40],"df1.iloc[1:3,2:]","df1.iloc[2:,3:]","df1.iloc[2:4,2:]","df1.loc[1:3,"门店2采购成本":"门店3采购成本"]","将以下表格读取后存放到数据框df1中,能实现把第二家门店和第三家门店的10月21日至10月23日的数据提取出来的语句是:( ) 日期 门店1采购成本 门店2采购成本 门店3采购成本 10月20日 56 62 78 10月21日 34 45 51 10月22日 88 93 98 10月23日 73 82 88",{"answer":43,"createTime":5,"id":6,"options":44,"question":19,"source":31,"type":32},[],[8,9,10,11],{"answer":46,"createTime":47,"id":48,"options":49,"question":54,"source":31,"type":32},[],"2024-07-04 13:19:03",157382679,[50,51,52,53],"df1.locate()","df1.to_excel()","df1.loc()","df1.to_csv()","对于数据框df1中的数据进行切片,使用以下哪一种方法( )",{"answer":56,"createTime":5,"id":57,"options":58,"question":63,"source":31,"type":32},[],157382680,[59,60,61,62],"df1.iloc[:,"门店2采购成本":"门店3采购成本"]","df1.loc[:,2:3]","df1.loc[:,"门店2采购成本":"门店3采购成本"]","df1.iloc[:,2:3]","将以下表格读取后存放到数据框df1中,把第二家门店和第三家门店的所有数据都提取出来的语句是:( ) 日期 门店1采购成本 门店2采购成本 门店3采购成本 10月20日 56 62 78 10月21日 34 45 51 10月22日 88 93 98 10月23日 73 82 88",{"answer":65,"createTime":5,"id":66,"options":67,"question":72,"source":31,"type":32},[],157382681,[68,69,70,71],"index","columns","size","ndim","以下哪一个是查看数据框DataFrame的元素个数( )",{"answer":74,"createTime":47,"id":75,"options":76,"question":81,"source":31,"type":32},[],157382682,[77,78,79,80],"iloc在传入的索引位置为区间时,前后均为闭区间,即起点和终点都包含进来","loc在传入的行索引名称为区间时,前后均为闭区间,即起点和终点都包含进来","loc方法的可读性好,大多数时候使用loc","loc内部可以传入条件表达式,而iloc不可以这样操作","关于数据框的loc和iloc方法的差异性描述,错误的是( )",{"answer":83,"createTime":5,"id":84,"options":85,"question":90,"source":31,"type":32},[],157382683,[86,87,88,89],"df1.loc[2,'门店2采购成本']=54","df1.iloc[1,3]=54","df1.iloc[1,2]=54","df1.iloc[1,'门店2采购成本']=54","将以下表格读取后存放到数据框df1中,现需要把门店2在10月21日采购成本45更新为54,哪项操作能够实现?( )日期 门店1采购成本 门店2采购成本 门店3采购成本10月20日 56 62 7810月21日 34 45 5110月22日 88 93 9810月23日 73 82 88",{"answer":92,"createTime":5,"id":93,"options":94,"question":99,"source":31,"type":32},[],157382684,[95,96,97,98],"read_excle","load_excel","read_excel","load_excle","以下哪项是DataFrame结构中读取excel文件的命令",{"answer":101,"createTime":5,"id":102,"options":103,"question":107,"source":31,"type":32},[],157382685,[104,105,106,51],"pandas.to_excel(df1)","df1.save_excel()","pandas.save_excel(df1)","将一个名为df1的数据框成功保存为excel的命令是以下哪个?( )"]