我有一个看起来像
的数据集datA
ID LINE_ID Fromdate Todate UniqueID
1 1 1/1/2015 2/3/2015 11
1 2 3/7/2015 3/9/2015 12
2 1 2/2/2015 2/8/2015 21
3 1 1/3/2013 1/8/2013 31
datB看起来像
ID LINE_ID Date UniqueID
1 1 1/1/2015 11
1 2 1/3/2015 12
1 3 2/2/2015 13
1 4 2/8/2015 14
1 5 3/8/2015 15
2 1 2/2/2015 21
2 2 2/3/2015 22
2 3 2/7/2015 23
2 4 2/8/2015 24
3 1 1/3/2013 31
3 2 1/7/2013 32
3 3 1/8/2013 33
3 4 1/9/2013 34
我想要做的是找到一种方法来合并两个数据集或找到一些方法来标记UniqueID中datA属于datB中的哪一行。例如，使用上面的两个数据集，我希望datC看起来像datB，其中添加了一列，UniqueID中的datA对应。
ID LINE_ID Date UniqueID UniqueID.A
1 1 1/1/2015 11 11
1 2 1/3/2015 12 11
1 3 2/2/2015 13 11
1 4 2/8/2015 14 NA
1 5 3/8/2015 15 12
2 1 2/2/2015 21 21
2 2 2/3/2015 22 21
2 3 2/7/2015 23 21
2 4 2/8/2015 24 21
3 1 1/3/2013 31 31
3 2 1/7/2013 32 31
3 3 1/8/2013 33 31
3 4 1/9/2013 34 NA
有人可以看到，添加到datB的新列是UniqueID datA datB中 func didBeginContact(contact: SKPhysicsContact) {
let firstBody: SKPhysicsBody
let secondBody: SKPhysicsBody
if contact.bodyA.categoryBitMask < contact.bodyB.categoryBitMask {
firstBody = contact.bodyA
secondBody = contact.bodyB
} else {
firstBody = contact.bodyB
secondBody = contact.bodyA
}
if (firstBody.categoryBitMask == PhysicsCategory.Goblin) && (secondBody.categoryBitMask == PhysicsCategory.Bullet) {
collisionWithBullet(firstBody.node as? SKSpriteNode, bullet: secondBody.node as? SKSpriteNode)
}
if (firstBody.categoryBitMask == PhysicsCategory.Goblin) && (secondBody.categoryBitMask == PhysicsCategory.player) {
collisionWithPlayer(firstBody.node as? SKSpriteNode, player: secondBody.node as? SKSpriteNode)
}
}
func collisionWithBullet(goblin: SKSpriteNode?, bullet:SKSpriteNode?){
guard let goblin = goblin, bullet = bullet else { return }
goblin.removeFromParent()
bullet.removeFromParent()
score += 1
scoreLbl.text = "\(score)"
if let explosion = SKEmitterNode(fileNamed: "Goblin Death Animation.sks") {
explosion.particlePosition = goblin.position
self.addChild(explosion)
}
if let fire = SKEmitterNode(fileNamed: "Goblin Death Animation 2.sks") {
fire.particlePosition = goblin.position
self.addChild(fire)
}
}
func collisionWithPlayer(goblin: SKSpriteNode?, player: SKSpriteNode?){
guard let goblin = goblin, player = player else { return }
let scoreDefault = NSUserDefaults.standardUserDefaults()
scoreDefault.setValue(score, forKey: "Score")
// synchronised not needed anymore
if (score > highscore){
let highscoreDefault = NSUserDefaults.standardUserDefaults()
highscoreDefault.setValue(score, forKey: "Highscore")
}
goblin.removeFromParent()
player.removeFromParent()
self.view?.presentScene(EndScene())
scoreLbl.removeFromSuperview()
}
的日期范围。{/ p>
有人对如何在R中执行此操作有任何指导吗？
答案 0 :(得分：1)
帮助实施。确保列是正确的类型并设置了键：
#Create a start and end columns formatted to dates
setDT(datB)[, ':='(c("start", "end"), as.IDate(Date, format="%m/%d/%Y"))]
#Format columns to dates
setDT(datA)[, ':='(c("Fromdate", "Todate"),
lapply(.SD, as.IDate, format="%m/%d/%Y")),
.SDcols=c("Fromdate", "Todate")]
#Set keys for matching intervals on
setkey(datA, Fromdate, Todate)
setkey(datB, start, end)
#Match on intervals
foverlaps(datB, datA, type="within")
答案 1 :(得分：0)
我编写了一个函数，可用于基于范围合并熊猫数据框： https://github.com/Chrisebell24/util/blob/master/custom_merge
import numpy as np
import pandas as pd
def merge_range(left, right, left_val, right_low, right_high):
'''
Parameters
----------
left : pandas dataframe
Left DataFrame that you are joining onto
right : pandas dataframe
Right DataFrame that has the ranged values
left_val : list
list of columns from left that contains numeric values
right_low : list
list of columns that you are matching to left_val
right_high : list
list of columns that you are matching to left_val
Returns
-------
Pandas dataframe
Example
-------
import numpy as np
np.random.seed(69)
df1, df2 = pd.DataFrame(), pd.DataFrame()
df1['LETTERS'] = ['a', 'b','c','d','e','f', 'g']
df1['RAND'] = np.random.randint(1,len(df1)*10, len(df1))
df2['COLOR'] = ['red', 'orange','yellow','green','blue','purple','brown']
df2['LOW'] = [i*10 for i in range(0, len(df2))]
df2['HIGH'] = [i*10 for i in range(1, 1+len(df2))]
merge_range(df1, df2, left_val=['RAND'], right_low=['LOW'], right_high= ['HIGH'])
LETTERS RAND COLOR LOW HIGH
0 a 55 purple 50 60
1 b 56 purple 50 60
2 c 21 yellow 20 30
3 d 50 purple 50 60
4 e 23 yellow 20 30
5 f 10 orange 10 20
6 g 57 purple 50 60
'''
true_args = True
for lv, rl, rh in zip(left_val, right_low, right_high):
a = left[lv].values
bl = right[rl].values
bh = right[rh].values
true_args *= (a[:, None] >= bl) & (a[:, None] < bh)
i, j = np.where(true_args)
df = pd.DataFrame(
np.column_stack([left.values[i], right.values[j]]),
columns=left.columns.append(right.columns)
)
if len(df.columns) - len(set(df.columns)) > 0:
print('Duplicate columns')
return df