我有data.frame
COL1 COL2
1 X X
2 X X
3 X Y
4 X X
5 Z X
如果列没有X，我需要获取适当的行号（在这种情况下为3和5）。我试图使用'sapply'通过“！=”检查数据，但我认为我还需要其他东西。
答案 0 :(得分：2)
以下是使用which的解决方案，该解决方案可以在任意数量的列上使用：
# example data
df <- data.frame(
col1 = c("X", "X", "X", "X", "Z"),
col2 = c("X", "X", "Z", "X", "X"),
stringsAsFactors = FALSE
)
# how to get rows without X
unique(sapply(df, function(x) which(x != "X")))
答案 1 :(得分：1)
这将起作用：
import pymysql, time, discord
from datetime import datetime
import warnings
warnings.simplefilter("ignore")
class BotEvents:
def __init__(self, *args, **kwargs):
@self.bot.event
async def on_ready():
self.log('\n', save=True)
self.log('-----------------------------------------', save=True)
self.log('Authorize successfully', save=True)
self.log('Authorized servers: ', save=True)
[self.log(' Name (id): %s (%s)' % (info.name, info.id), save=True) for info in self.bot.guilds]
self.log('-----------------------------------------', save=True)
await self.bot.loop.create_task(self.female_logic())
def counter(self, server):
db_conn, db_cursor = self.connect_db()
result = db_cursor.execute("SELECT `user_id` FROM `users` WHERE server_id = '{}'".format(server.id))
members = []
if result != 0:
for x in range(result):
members.append(db_cursor.fetchone()[0])
db_conn.close()
while self.run_c:
roles = []
member_role = []
db_conn, db_cursor = self.connect_db()
result = db_cursor.execute("SELECT `role_id`, `min_exp` FROM `auto_roles` WHERE server_id = '{}' ORDER BY `min_exp`".format(server.id))
if result != 0:
info = db_cursor.fetchone()
member_role = [str(info[0]), int(info[1])]
for x in range(result - 1):
info = db_cursor.fetchone()
roles.append([str(info[0]), int(info[1])])
db_conn.close()
for member in server.members:
if member != self.bot.user:
db_conn, db_cursor = self.connect_db()
if str(member.id) not in members:
db_cursor.execute("INSERT INTO `users` (`server_id`, `user_name`, `user_id`, `last_update_online`, `last_update`) VALUES ('{0}', '{1}', '{2}', '{3}', '{3}')".format(server.id, member.name.replace("'", ''), member.id, time.time()))
db_conn.commit()
members.append(str(member.id))
self.log(' [%s] Added user: %s' % (server.name, member.name), save=True)
else:
db_cursor.execute("SELECT `member`, `balance`, `online_time`, `last_update_online`, `experience`, `last_update`, `autorole` FROM `users` WHERE (user_id = '{}' AND server_id = '{}')".format(member.id, server.id))
info = db_cursor.fetchone()
if info is not None:
info = {
'member':bool(info[0]),
'balance':int(info[1]),
'online_time':int(info[2]),
'last_update_online':int(info[3]),
'experience':int(info[4]),
'last_update':int(info[5]),
'autorole':info[6]
}
if int(time.time()) - info['last_update_online'] > 60:
if str(member.status) in ['online', 'idle', 'dnd']:
db_cursor.execute("UPDATE `users` SET online_time = {}, last_update_online = {} WHERE (user_id = '{}' AND server_id = '{}')".format(
info['online_time'] + 1,
time.time(),
member.id,
server.id))
db_conn.commit()
self.log('[%s] Updated online for user: %s ' % (server.name, member.name), save=True)
if int(time.time()) - info['last_update'] > 60:
if member.voice is not None:
db_cursor.execute("UPDATE `users` SET balance = {}, experience = {}, last_update = {} WHERE (user_id = '{}' AND server_id = '{}')".format(
info['balance'] + self.gold_per_minut,
info['experience'] + self.exp_per_minut,
time.time(),
member.id,
server.id))
db_conn.commit()
self.log('[%s] Updated balance, experience for user: %s ' % (server.name, member.name), save=True)
if len(member_role) != 0:
if not info['member'] and info['experience'] >= member_role[1]:
role_o = discord.utils.get(server.roles, id=int(member_role[0]))
if role_o not in member.roles:
self.bot.loop.create_task(member.add_roles(role_o))
db_cursor.execute("UPDATE `users` SET member = {} WHERE (user_id = '{}' AND server_id = '{}')".format(True, member.id, server.id))
db_conn.commit()
new_role = ''
for role in roles:
if role[1] <= info['experience']:
new_role = role[0]
if new_role != '' and new_role != info['autorole']:
if info['autorole'] != '0':
role_o = discord.utils.get(server.roles, id=int(info['autorole']))
if role_o in member.roles:
self.bot.loop.create_task(member.remove_roles(role_o))
self.log('[%s] For user %s deleted old role %s(%s)' % (
server.name,
member.name,
role_o.name,
role_o.id) , save=True)
time.sleep(2)
role_o = discord.utils.get(server.roles, id=int(new_role))
if role_o is not None:
if role_o not in member.roles:
db_cursor.execute("UPDATE `users` SET autorole = '{}' WHERE (user_id = '{}' AND server_id = '{}')".format(new_role, member.id, server.id))
db_conn.commit()
self.bot.loop.create_task(member.add_roles(role_o))
self.log('[%s] For user %s added role %s(%s)' % (server.name, member.name, role_o.name, role_o.id), save=True)
db_conn.close()
答案 2 :(得分：1)
您接近了，将sapply与原始函数!=一起使用的想法基本上是正确的。
以下内容返回逻辑矩阵。
sapply(dat, `!=`, "X")
# COL1 COL2
#[1,] FALSE FALSE
#[2,] FALSE FALSE
#[3,] FALSE TRUE
#[4,] FALSE FALSE
#[5,] TRUE FALSE
如果需要行号，请将其包装在which中，并将参数arr.ind设置为TRUE。
which(sapply(dat, `!=`, "X"), arr.ind = TRUE)
# row col
#[1,] 5 1
#[2,] 3 2
编辑。
发布了几种解决方案，这是比较测试。
由于OP表示可能有100列的数据集，所以我测试了两个不同的数据集，即问题中发布的数据集和更大的数据集。
函数RuiJaap是Rui，其中包含Jaap注释中的建议。
Rui <- function(DF, value = "X")
which(sapply(DF, `!=`, value), arr.ind = TRUE)
DanY <- function(DF, value = "X")
unique(sapply(DF, function(x) which(x != value)))
Jaap <- function(DF, value = "X")
which(!!rowSums(DF != value))
RuiJaap <- function(DF, value = "X")
which(dat != "X", arr.ind = TRUE)
library(ggplot2)
library(microbenchmark)
mb1 <- microbenchmark(Rui = Rui(dat),
RuiJaap = RuiJaap(dat),
Jaap = Jaap(dat),
DanY = DanY(dat),
times = 1e3)
mb2 <- microbenchmark(Rui = Rui(dat2),
RuiJaap = RuiJaap(dat2),
Jaap = Jaap(dat2),
DanY = DanY(dat2),
times = 1e2)
autoplot(mb1)
autoplot(mb2)
对于小型数据集，DanY更快，而对于大型数据集，RuiJaap是最快的。
数据。
dat <- read.table(text = "
COL1 COL2
1 X X
2 X X
3 X Y
4 X X
5 Z X
", header = TRUE)
set.seed(1)
dat2 <- matrix("X", nrow = 20, ncol = 100)
dat2[sample(2000, 100)] <- "Y"
dat2 <- as.data.frame(dat2)
答案 3 :(得分：1)
这是一个tidyverse解决方案，可以在任意数量的列上使用
library(tidyverse)
df <- tibble(
col1 = c("X", "X", "X", "X", "Z"),
col2 = c("X", "X", "Z", "X", "X"),
col3 = c("X", "X", "Z", "Z", "X"),
)
filter_all(df, any_vars(. != "X"))
哪个返回：
# A tibble: 3 x 3
col1 col2 col3
<chr> <chr> <chr>
1 X Z Z
2 X X Z
3 Z X X
答案 4 :(得分：1)
这是基本的R解决方案，适用于任意数量的列-
which(rowSums(df == "X") != ncol(df))