比较2 datetime64 [ns]数据框列

Question

I have two date columns namely date1 and date2. I am trying to select rows which have date1 later than date2 I tried to

print df[df.loc[df['date1']>df['date2']]]

but I recieved an error

ValueError: Boolean array expected for the condition, not float64

Answer 1

In either case, the idea is to retrieve a boolean mask. This boolean mask will then be used to index into the dataframe and retrieve corresponding rows. First, generate a mask:

mask = df['date1'] > df['date2']

Now, use this mask to index df :

df = df.loc[mask]

This can be written in a single line.

df = df.loc[df['date1'] > df['date2']]

You do not need to perform another level of indexing after this, df now has your final result. I recommend loc if you are planning to perform operations and reassignment on this filtered dataframe, because loc always returns a copy, while plain indexing returns a view.

---

Below are some more methods of doing the same thing:

Option 1
df.query

df.query('date1 > date2')

---

Option 2
df.eval

df[df.eval('date1 > date2')]

---

If your columns are not dates, you might as well cast them now. Use pd.to_datetime :

df.date1 = pd.to_datetime(df.date1)
df.date2 = pd.to_datetime(df.date2)

Or, when loading your CSV, make sure to set the parse_dates switch on:

df = pd.read_csv(..., parse_dates=['date1, date2'])