问题
I have 2 columns in my pandas data frame, and I want to calculate the business dates between them.
Data:
ID On hold Off Hold
101 09/15/2017 09/16/2017
102 NA NA
103 09/22/2017 09/26/2017
104 10/12/2017 10/30/2017
105 NA NA
106 08/05/2017 08/06/2017
107 08/08/2017 08/03/2017
108 NA NA
I tried the below code using busday_count from numpy:
df1['On hold'] = pd.to_datetime(df1['On hold'])
df1['Off Hold'] = pd.to_datetime(df1['Off Hold'])
np.busday_count(df1['On hold'].values.astype('datetime64[D]'),df1['Off Hold'].values.astype('datetime64[D]'))
also,
np.where(pd.notnull(df1['On hold']),np.busday_count(df1['On hold'].values.astype('datetime64[D]'),
df1['Off Hold'].values.astype('datetime64[D]')),0)
The error was :
Cannot compute a business day count with a NaT (not-a-time) date
Any help will be appreciated :)
回答1:
You can try the below:
f = df1.dropna()
f['days'] = np.busday_count(pd.to_datetime(f['On hold']).values.astype('datetime64[D]'), \
pd.to_datetime(f['Off hold']).values.astype('datetime64[D]'))
df1.merge(f[['ID', 'days']],on='ID', how='left')
回答2:
Using the pd.bdate_range method:
pd.bdate_range(df['On Hold'], df['Off Hold'], freq = 'B')
回答3:
Try to drop NA first before you do bus day count. You can drop all the NA by using the following.
new_df = df.dropna()
来源:https://stackoverflow.com/questions/46903848/find-the-business-days-between-two-columns-in-a-pandas-dataframe-which-contain