我正在读取一个文件，输出应该看起来像下面那个，忽略实际表格我的小时，分钟和秒的值都是关闭的钱，这应该通过四舍五入来计算分钟;我已经尝试了很多方法来解决这个问题，这是我的最后一招。
+--------------+------------------------------+---+---------+--------+
| Phone number | Name | # |Duration | Due |
+--------------+------------------------------+---+---------+--------
|(780) 123 4567|Ameneh Gholipour Shahraki |384|55h07m53s|$ 876.97|**
|(780) 123 6789|Stuart Johnson |132|17h53m19s|$ 288.81|
|(780) 321 4567|Md Toukir Imam |363|49h52m12s|$ 827.48|++
|(780) 432 1098|Hamman Samuel |112|16h05m09s|$ 259.66|
|(780) 492 2860|Osmar Zaiane |502|69h27m48s|$1160.52|**
|(780) 789 0123|Elham Ahmadi |259|35h56m10s|$ 596.94|
|(780) 876 5432|Amir Hossein Faghih Dinevari |129|17h22m32s|$ 288.56|
|(780) 890 7654|Weifeng Chen |245|33h48m46s|$ 539.41|
|(780) 987 6543|Farrukh Ahmed |374|52h50m11s|$ 883.72|**
+--------------+------------------------------+---+---------+--------+
| Total dues | $ 5722.07|
+--------------+-----------------------------------------------------+
这是我的代码，我在使用time（）和due（）函数时遇到的麻烦最多
from collections import Counter
customers=open('customers.txt','r')
calls=open('calls.txt.','r')
def main():
customers=open('customers.txt','r')
calls=open('calls.txt.','r')
print("+--------------+------------------------------+---+---------+--------+")
print("| Phone number | Name | # |Duration | Due |")
print("+--------------+------------------------------+---+---------+--------+")
phone_sorter()
number_calls()
time()
due()
def phone_sorter():
sorted_no={}
for line in customers:
rows=line.split(";")
sorted_no[rows[1]]=rows[0]
for value in sorted(sorted_no.values()):
for key in sorted_no.keys():
if sorted_no[key] == value:
print(sorted_no[key],key)
def number_calls():
no_calls={}
for line in calls:
rows=line.split(";")
if rows[1] not in no_calls:
no_calls[rows[1]]=1
else:
no_calls[rows[1]]+=1
s=sorted(no_calls.keys())
for key in s:
print(no_calls[key])
def time():
calls=open('calls.txt.','r')
n_list=[]
d={}
for line in calls:
rows=line.split(";")
d[rows[1]]=rows[3]
if rows[1] not in d:
d[rows[1]]=rows[3]
else:
d[rows[1]]+=rows[3]
x=sorted(d.keys())
for value in x:
m, s = divmod(int(value), 60)
h, m = divmod(m, 60)
print("%d:%02d:%02d" % (h, m, s))
def due():
calls=open('calls.txt.','r')
d2={}
for line in calls:
rows=line.split(";")
d2[rows[1]]=float(rows[3])*float(rows[4])
if rows[1] not in d2:
d2[rows[1]]=float(rows[3])*float(rows[4])
else:
d2[rows[1]]+=float(rows[3])*float(rows[4])
x=sorted(d2.keys())
for key in x:
print(d2[key])
print(sum(d2.values()))
main()
这是我在pastebin中阅读的文件的链接：http://pastebin.com/RSMnXDtq
第一列是电话号码。此编号必须格式化为（999）999 9999。
第二列是名称，宽度必须为30个字符。
第三列是来自相关手机的来电数量。它应该是3位数。
第四列是来自相关电话的来电总持续时间。此持续时间应格式如下：99h99m99s小时，分钟和秒。如果小于10，则分钟和秒的前缀应为0。
第五列是根据每次通话所附的费率计算的通话金额。请注意，每次通话的持续时间应向上舍入到分钟，以便使用每分钟的费率。此金额应打印7个位置，小数点后仅2个。
答案 0 :(得分：0)
以下是使用pandas的解决方案：
from pandas import np, read_csv
#
# Load and process call data
#
def get_data(calls_fname, custs_fname):
# load call data
calls = read_csv(
calls_fname,
sep = ";",
names = ["session", "phone", "to", "seconds", "rate"],
header = None
)
# calculate cost per call (time rounded up to the next minute)
calls["cost"] = np.ceil(calls["seconds"] / 60.) * calls["rate"]
# add a call-count column
# (I think there is a better way to do this using np.size in
# the .groupby, but I haven't been able to figure it out)
calls["count"] = 1
# find per-cust totals
calls = calls.groupby(["phone"]).agg({"seconds":np.sum, "cost":np.sum, "count":np.sum})
# load customer data
custs = read_csv(
custs_fname,
sep = ";",
names = ["phone", "name"],
header = None,
index_col = 0 # index by phone number
)
# join to find customer name
return calls.join(custs, sort=False).reset_index()
#
# output formatting functions
#
def phone_str(i):
"""
Convert int 1234567890 to str "(123) 456 7890"
"""
s = str(i).zfill(10)
return "({}) {} {}".format(s[0:3], s[3:6], s[6:10])
def time_str(i):
"""
Convert int 3662 to str " 1h01m02s"
"""
m, s = divmod(i, 60)
h, m = divmod(m, 60)
return "{:>2d}h{:02d}m{:02d}s".format(h, m, s)
def make_table(totals):
header = (
"+--------------+------------------------------+---+---------+--------+\n"
"| Phone number | Name | # |Duration | Due |\n"
"+--------------+------------------------------+---+---------+--------+\n"
)
rows = [
"|{}|{:<30}|{:>3d}|{}|${:7.2f}|\n"
.format(
phone_str(row["phone" ]),
row["name" ],
row["count" ],
time_str (row["seconds"]),
row["cost" ]
)
for i,row in totals.iterrows()
]
total_dues = np.sum(totals["cost"])
footer = (
"+--------------+------------------------------+---+---------+--------+\n"
"| Total dues | ${:10.2f}|\n"
"+--------------+-----------------------------------------------------+"
.format(total_dues)
)
return header + "".join(rows) + footer
def main():
totals = get_data("calls.txt", "customers.txt")
print(make_table(totals))
if __name__ == "__main__":
main()
将您的pastebin链接中的数据用作calls.txt，将以下内容用作customers.txt：
7801236789;Stuart Johnson
7804321098;Hamman Samuel
7803214567;Md Toukir Imam
7804922860;Osmar Zaiane
7801234567;Ameneh Gholipour Shahraki
7807890123;Elham Ahmadi
7808765432;Amir Hossein Faghih Dinevari
7808907654;Weifeng Chen
7809876543;Farrukh Ahmed
它产生
+--------------+------------------------------+---+---------+--------+
| Phone number | Name | # |Duration | Due |
+--------------+------------------------------+---+---------+--------+
|(780) 123 4567|Ameneh Gholipour Shahraki |384|55h07m53s|$ 876.97|
|(780) 123 6789|Stuart Johnson |132|17h53m19s|$ 288.81|
|(780) 321 4567|Md Toukir Imam |363|49h52m12s|$ 827.48|
|(780) 432 1098|Hamman Samuel |112|16h05m09s|$ 259.66|
|(780) 492 2860|Osmar Zaiane |502|69h27m48s|$1160.52|
|(780) 789 0123|Elham Ahmadi |259|35h56m10s|$ 596.94|
|(780) 876 5432|Amir Hossein Faghih Dinevari |129|17h22m32s|$ 288.56|
|(780) 890 7654|Weifeng Chen |245|33h48m46s|$ 539.41|
|(780) 987 6543|Farrukh Ahmed |374|52h50m11s|$ 883.72|
+--------------+------------------------------+---+---------+--------+
| Total dues | $ 5722.07|
+--------------+-----------------------------------------------------+