我试图在一个大数据集中计算每小时的一些实例。下面的代码似乎在Python2.7上运行良好,但我不得不将其升级到3.x最新版本的python,并在Anaconda上更新了所有包。当我试图执行程序时,我得到了如下的str
错误
代码:
import pandas as pd
from datetime import datetime,time
import numpy as np
fn = r'00_input.csv'
cols = ['UserId', 'UserMAC', 'HotspotID', 'StartTime', 'StopTime']
df = pd.read_csv(fn, header=None, names=cols)
df['m'] = df.StopTime + df.StartTime
df['d'] = df.StopTime - df.StartTime
# 'start' and 'end' for the reporting DF: `r`
# which will contain equal intervals (1 hour in this case)
start = pd.to_datetime(df.StartTime.min(), unit='s').date()
end = pd.to_datetime(df.StopTime.max(), unit='s').date() + pd.Timedelta(days=1)
# building reporting DF: `r`
freq = '1H' # 1 Hour frequency
idx = pd.date_range(start, end, freq=freq)
r = pd.DataFrame(index=idx)
r['start'] = (r.index - pd.datetime(1970,1,1)).total_seconds().astype(np.int64)
# 1 hour in seconds, minus one second (so that we will not count it twice)
interval = 60*60 - 1
r['LogCount'] = 0
r['UniqueIDCount'] = 0
for i, row in r.iterrows():
# intervals overlap test
# https://en.wikipedia.org/wiki/Interval_tree#Overlap_test
# i've slightly simplified the calculations of m and d
# by getting rid of division by 2,
# because it can be done eliminating common terms
u = df[np.abs(df.m - 2*row.start - interval) < df.d + interval].UserID
r.ix[i, ['LogCount', 'UniqueIDCount']] = [len(u), u.nunique()]
r['Date'] = pd.to_datetime(r.start, unit='s').dt.date
r['Day'] = pd.to_datetime(r.start, unit='s').dt.weekday_name.str[:3]
r['StartTime'] = pd.to_datetime(r.start, unit='s').dt.time
r['EndTime'] = pd.to_datetime(r.start + interval + 1, unit='s').dt.time
#r.to_csv('results.csv', index=False)
#print(r[r.LogCount > 0])
#print (r['StartTime'], r['EndTime'], r['Day'], r['LogCount'], r['UniqueIDCount'])
rout = r[['Date', 'StartTime', 'EndTime', 'Day', 'LogCount', 'UniqueIDCount'] ]
#print rout
rout.to_csv('o_1_hour.csv', index=False, header=False
(第页)
在何处进行更改以获得无错误执行
错误:
File "C:\Program Files\Anaconda3\lib\site-packages\pandas\core\ops.py", line 686, in <lambda>
lambda x: op(x, rvalues))
TypeError: unsupported operand type(s) for -: 'str' and 'str'
谢谢你的帮助,提前谢谢
df['d'] = df.StopTime - df.StartTime
正在尝试从另一个字符串中减去一个字符串。我不知道你的数据是什么样子的,但很可能你想把StopTime
和StartTime
解析为日期。试试看而不是
df = pd.read_csv(fn, header=None, names=cols)
。我认为您需要将
header=0
更改为select first row to header,然后用listcols
替换列名。如果仍然存在问题,则需要^{} ,因为
StartTime
和StopTime
中的某些值是字符串,被解析为NaN
,替换为0
最后一个转换列为int
:无变化:
ix
在上一版本的pandas中不推荐使用,因此请使用loc
,并且列名在[]
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