# Holidays

In \[1]:

```python
import pandas as pd
df = pd.read_csv("apple_stock_price_nodate.csv")
df.head()
```

Out\[1]:

|   | Open       | High       | Low        | Close      | Adj Close  | Volume   |
| - | ---------- | ---------- | ---------- | ---------- | ---------- | -------- |
| 0 | 190.679993 | 191.960007 | 189.559998 | 191.610001 | 188.737030 | 15989400 |
| 1 | 192.449997 | 193.660004 | 192.050003 | 193.000000 | 190.106216 | 18697900 |
| 2 | 193.059998 | 194.850006 | 192.429993 | 194.820007 | 191.898926 | 16709900 |
| 3 | 194.610001 | 195.960007 | 193.610001 | 194.210007 | 191.298080 | 19076000 |
| 4 | 194.990005 | 195.190002 | 190.100006 | 190.979996 | 188.116501 | 24024000 |

**Using 'B' frequency is not going to help because 4th July was holiday and 'B' is not taking that into account. It only accounts for weekends**

## Generate US holidays calendar frequency <a href="#using-custombusinessday-to-generate-us-holidays-calendar-frequency" id="using-custombusinessday-to-generate-us-holidays-calendar-frequency"></a>

In \[2]:

```python
from pandas.tseries.holiday import USFederalHolidayCalendar
from pandas.tseries.offsets import CustomBusinessDay

us_cal = CustomBusinessDay(calendar=USFederalHolidayCalendar())

rng = pd.date_range(start="2018-07-23",periods=df.shape[0],freq=us_cal)
rng
```

Out\[2]:

```python
DatetimeIndex(['2018-07-23', '2018-07-24', '2018-07-25', '2018-07-26',
               '2018-07-27', '2018-07-30', '2018-07-31', '2018-08-01',
               '2018-08-02', '2018-08-03',
               ...
               '2019-07-10', '2019-07-11', '2019-07-12', '2019-07-15',
               '2019-07-16', '2019-07-17', '2019-07-18', '2019-07-19',
               '2019-07-22', '2019-07-23'],
              dtype='datetime64[ns]', length=252, freq='C')
```

In \[5]:

```python
df.set_index(rng,inplace=True)
df.head()
```

Out\[5]:

|            | Open       | High       | Low        | Close      | Adj Close  | Volume   |
| ---------- | ---------- | ---------- | ---------- | ---------- | ---------- | -------- |
| 2018-07-23 | 190.679993 | 191.960007 | 189.559998 | 191.610001 | 188.737030 | 15989400 |
| 2018-07-24 | 192.449997 | 193.660004 | 192.050003 | 193.000000 | 190.106216 | 18697900 |
| 2018-07-25 | 193.059998 | 194.850006 | 192.429993 | 194.820007 | 191.898926 | 16709900 |
| 2018-07-26 | 194.610001 | 195.960007 | 193.610001 | 194.210007 | 191.298080 | 19076000 |
| 2018-07-27 | 194.990005 | 195.190002 | 190.100006 | 190.979996 | 188.116501 | 24024000 |

**You can define your own calendar using AbstractHolidayCalendar as shown below. USFederalHolidayCalendar is the only calendar available in pandas library and it serves as an example for those who want to write their own custom calendars. Here is the link for USFederalHolidayCalendar implementation** <https://github.com/pandas-dev/pandas/blob/master/pandas/tseries/holiday.py>

In \[12]:

```python
from pandas.tseries.holiday import AbstractHolidayCalendar, nearest_workday, Holiday
class myCalendar(AbstractHolidayCalendar):
    rules = [
        Holiday('My Birth Day', month=5, day=13),#, observance=nearest_workday),
    ]
    
my_bday = CustomBusinessDay(calendar=myCalendar())

pd.date_range('5/1/2019','6/1/2019',freq=my_bday)
```

Out\[12]:

```python
DatetimeIndex(['2019-05-01', '2019-05-02', '2019-05-03', '2019-05-06',
               '2019-05-07', '2019-05-08', '2019-05-09', '2019-05-10',
               '2019-05-14', '2019-05-15', '2019-05-16', '2019-05-17',
               '2019-05-20', '2019-05-21', '2019-05-22', '2019-05-23',
               '2019-05-24', '2019-05-27', '2019-05-28', '2019-05-29',
               '2019-05-30', '2019-05-31'],
              dtype='datetime64[ns]', freq='C')
```

### **Weekend in egypt is Friday and Saturday. Sunday is just a normal weekday and you can handle this custom week schedule using CystomBysinessDay with** weekmask **as shown below** <a href="#weekend-in-egypt-is-friday-and-saturday.-sunday-is-just-a-normal-weekday-and-you-can-handle-this-cus" id="weekend-in-egypt-is-friday-and-saturday.-sunday-is-just-a-normal-weekday-and-you-can-handle-this-cus"></a>

In \[15]:

```python
egypt_weekdays = "Sun Mon Tue Wed Thu"

b = CustomBusinessDay(weekmask=egypt_weekdays)

pd.date_range(start="7/1/2018",periods=20,freq=b)
```

Out\[15]:

```python
DatetimeIndex(['2018-07-01', '2018-07-02', '2018-07-03', '2018-07-04',
               '2018-07-05', '2018-07-08', '2018-07-09', '2018-07-10',
               '2018-07-11', '2018-07-12', '2018-07-15', '2018-07-16',
               '2018-07-17', '2018-07-18', '2018-07-19', '2018-07-22',
               '2018-07-23', '2018-07-24', '2018-07-25', '2018-07-26'],
              dtype='datetime64[ns]', freq='C')
```

### **You can also add holidays to this custom business day frequency**[¶](broken://pages/-MlKopKBr_62anuJODSv#You-can-also-add-holidays-to-this-custom-business-day-frequency) <a href="#you-can-also-add-holidays-to-this-custom-business-day-frequency" id="you-can-also-add-holidays-to-this-custom-business-day-frequency"></a>

In \[17]:

```python
b = CustomBusinessDay(holidays=['2018-08-04', '2018-08-05'], weekmask=egypt_weekdays)

pd.date_range(start="8/1/2018",periods=20,freq=b)
```

Out\[17]:

```python
DatetimeIndex(['2018-08-01', '2018-08-02', '2018-08-06', '2018-08-07',
               '2018-08-08', '2018-08-09', '2018-08-12', '2018-08-13',
               '2018-08-14', '2018-08-15', '2018-08-16', '2018-08-19',
               '2018-08-20', '2018-08-21', '2018-08-22', '2018-08-23',
               '2018-08-26', '2018-08-27', '2018-08-28', '2018-08-29'],
              dtype='datetime64[ns]', freq='C')
```

### **Mathematical operations on date object using custom business day**[¶](broken://pages/-MlKopKBr_62anuJODSv#Mathematical-operations-on-date-object-using-custom-business-day) <a href="#mathematical-operations-on-date-object-using-custom-business-day" id="mathematical-operations-on-date-object-using-custom-business-day"></a>

In \[18]:

```python
from datetime import datetime
dt = datetime(2017,7,9)
dt
```

Out\[18]:

```python
datetime.datetime(2017, 7, 9, 0, 0)
```

Out\[19]:

```python
Timestamp('2017-07-10 00:00:00')
```


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