在熊猫中按日期字符串排序-Python 2.7

Question

I have .csv data that I want to sort by it's date column. My date format is of the following:

Week,Quarter,Year: So WK01Q12001 for example.

When I .sort() my dataframe on this column, the resulting is sorted like:

WK01Q12001, WK01Q12002, WK01Q12003, WK01Q22001, WK01Q22002, WK01Q22003, ... WK02Q12001, WK02Q12002...

for example. This makes sense because its sorting the string in ascending order.

But I need my data sorted chronologically such that the result is like the following:

WK01Q12001, WK02Q12001, WK03Q12001, WK04Q12001, ... , WK01Q22001, WK02Q22001, ... WK01Q12002, WK02Q22002 ...

How can I sort it this way using pandas? Perhaps sorting the string in reverse? (right to left) or creating some kind of datetime object?

I have also tried using Series() : pd.Series([pd.to_datetime(d) for d in weeklyData['Date']]) But the result is same as the above .sort() method.

UPDATE: My DataFrame is similar in format to an excel sheet and currently looks like the following. I want to sort chronologically by 'Date'.

Date          Price     Volume
WK01Q12001    32        500
WK01Q12002    43        400
WK01Q12003    55        300
WK01Q12004    58        350
WK01Q22001    33        480
WK01Q22002    40        450
.
.
.
WK13Q42004    60        400

Answer 1

You can add a new column to your dataframe containing the date components as a list.

eg

a = ["2001", "Q2", "WK01"]
b = ["2002", "Q2", "WK01"]
c = ["2002", "Q2", "WK02"]

So, you can apply a function to your data frame to do this...

def tolist(x):
    g = re.match(r"(WK\d{2})(Q\d)(\d{4})", str(x))
    return [g.group(3), g.group(2), g.group(1)]

then...

 df['datelist'] = df['Date'].apply(tolist)

which gives you your date as a list arranged in the order of importance...

         Date  Price  Volume          datelist
0  WK01Q12001     32     500  [2001, Q1, WK01]
1  WK01Q12002     22     400  [2002, Q1, WK01]
2  WK01Q12003     42     500  [2003, Q1, WK01]

When comparing lists of equal length in Python the comparison operators behave well. So, you can use the standard DataFrame sort to order your data.

So the default sorting in a Pandas series will work correctly when you do...

df.sort('datelist')

Answer 2

Use str.replace to change the order of the keys first:

s = "WK01Q12001, WK01Q12002, WK01Q12003, WK01Q22001, WK01Q22002, WK01Q22003, WK02Q12001, WK02Q12002"
date = map(str.strip, s.split(","))
df = pd.DataFrame({"date":date, "value":range(len(date))})
df["date2"] = df.date.str.replace(r"WK(\d\d)Q(\d)(\d{4})", r"\3Q\2WK\1")
df.sort("date2")

Answer 3

I was also able to accomplish this Date reformatting very easily using SQL. When I first query my data, I did SELECT *, RIGHT([Date], 4) + SUBSTRING([Date], 5, 2) + LEFT([Date], 4) As 'SortedDate' FROM [Table] ORDER BY 'SortedDate' ASC .

Use the right tool for the job!