R-复制到行时的数字舍入错误
下面是我如何创建一个空数据框,我打算从数据源一次填充一行R-复制到行时的数字舍入错误,r,dataframe,rounding,int64,R,Dataframe,Rounding,Int64,下面是我如何创建一个空数据框,我打算从数据源一次填充一行 numTweets=31 finalDataFrame = as.data.frame( matrix(NA, numTweets-1, 23), stringsAsFactors=FALSE) names(finalDataFrame) = c( "TweetID", "TweetTime", "Text", "Source", "UserID", "Username",
numTweets=31
finalDataFrame = as.data.frame( matrix(NA, numTweets-1, 23), stringsAsFactors=FALSE)
names(finalDataFrame) = c( "TweetID", "TweetTime", "Text", "Source",
"UserID", "Username", "Screenname", "FollowerCount", "FriendCount",
"Location", "Latitude", "Longitude", "ReplyTweetID", "ReplyUserID",
"ReplyScreenname", "RetweetID", "RetweetCreated", "RetweetUsername",
"RetweetScreename", "RetweetLocation", "RetweetFollowers", "RetweetFriends",
"RetweetSource" )
下面是我插入的一行的示例
print( thisRow, row.names=FALSE )
TweetID TweetTime Text
877010425019158529 Tue Jun 20 03:49:14 +0000 2017 @OmniDestiny I would recommend trying to find the facebook group for evergreen because i think their school facebook page got shut down.
Source UserID Username Screenname FollowerCount FriendCount Location Latitude Longitude ReplyTweetID ReplyUserID ReplyScreenname RetweetID
<a href="http://twitter.com" rel="nofollow">Twitter Web Client</a> 843603187298779137 Albert HellhoyZ 4 72 Bellevue, WA 0 0 876742560328417281 4726147296 OmniDestiny NA
RetweetCreated RetweetUsername RetweetScreename RetweetLocation RetweetFollowers RetweetFriends RetweetSource
NA NA NA NA NA NA NA
许多价值观变得怪异。例如,此行将ReplyTweetID值(一个int64值)完美地显示为876742560328417281,但当我在finalDataFrame的R中查看它时
finalDataFrame[1, "ReplyTweetID" ]
[1] 0.00000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000046816189162956993
>
我不确定是什么导致了这种剧烈的变化。有什么想法吗
编辑:我很确定这是因为值是int64,而矩阵不喜欢它。然而,有没有一种方法来准备矩阵呢?我也可以在开始制作“thisRow”时使用toString(IDVALUEHERE),但这似乎不必要
finalDataFrame[1, "ReplyTweetID" ]
[1] 0.00000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000046816189162956993
>