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Articles by AmitDiwan
Page 61 of 840
Python Pandas - Indicate whether the date in DateTimeIndex is the last day of the month
To check whether dates in a DateTimeIndex correspond to the last day of their respective months, use the is_month_end property. This returns a boolean array indicating which dates fall on month-end dates. Syntax DateTimeIndex.is_month_end Creating a DateTimeIndex First, let's create a DateTimeIndex with various dates ? import pandas as pd # Create DateTimeIndex with 15-day intervals datetimeindex = pd.date_range('2021-9-15 06:40:35', periods=6, tz='Australia/Adelaide', freq='15D') print("DateTimeIndex...") print(datetimeindex) DateTimeIndex... DatetimeIndex(['2021-09-15 06:40:35+09:30', '2021-09-30 06:40:35+09:30', '2021-10-15 06:40:35+10:30', ...
Read MorePython Pandas - Indicate whether the date in DateTimeIndex is the first day of the month
To check whether the date in DateTimeIndex is the first day of the month, use the DateTimeIndex.is_month_start property. This boolean property returns True for dates that fall on the first day of their respective months. Syntax DateTimeIndex.is_month_start Creating a DateTimeIndex First, let's create a DateTimeIndex with various dates to demonstrate the functionality − import pandas as pd # Create a DateTimeIndex with period 6 and frequency as 5 days # The timezone is Australia/Adelaide datetimeindex = pd.date_range('2021-9-21 02:30:50', periods=6, tz='Australia/Adelaide', freq='5D') # Display DateTimeIndex print("DateTimeIndex...") print(datetimeindex) DateTimeIndex... ...
Read MorePython Pandas - Extract the frequency object as a string from the DateTimeIndex
To extract the frequency object as a string from the DateTimeIndex, use the DateTimeIndex.freqstr property in Pandas. This property returns the frequency as a string representation, which is useful for displaying or storing the frequency information. Creating a DateTimeIndex with Frequency First, let's create a DateTimeIndex with a specific frequency ? import pandas as pd # Create DatetimeIndex with period 6 and frequency as D (daily) # The timezone is Australia/Adelaide datetimeindex = pd.date_range('2021-10-20 02:30:50', periods=6, tz='Australia/Adelaide', freq='D') print("DateTimeIndex...") print(datetimeindex) DateTimeIndex... DatetimeIndex(['2021-10-20 02:30:50+10:30', '2021-10-21 02:30:50+10:30', ...
Read MorePython Pandas - Extract the frequency from the DateTimeIndex
To extract the frequency from the DateTimeIndex, use the DateTimeIndex.freq property in Pandas. This property returns the frequency object associated with the DateTimeIndex, which is useful for understanding the time intervals between consecutive dates. Syntax DateTimeIndex.freq Creating a DateTimeIndex with Frequency First, let's create a DateTimeIndex with a specific frequency to demonstrate the extraction ? import pandas as pd # Create DateTimeIndex with period 6 and frequency as D (day) # The timezone is Australia/Adelaide datetimeindex = pd.date_range('2021-10-20 02:30:50', periods=6, tz='Australia/Adelaide', freq='D') # Display DateTimeIndex print("DateTimeIndex...") print(datetimeindex) ...
Read MorePython Pandas - Extract the timezone from the DateTimeIndex with specific time series frequency
To extract the timezone from a DateTimeIndex with specific time series frequency, use the DateTimeIndex.tz property. This is useful when working with time series data across different geographical regions. Syntax The basic syntax to extract timezone information ? DateTimeIndex.tz Creating DateTimeIndex with Timezone First, let's create a DateTimeIndex with timezone information and specific frequency ? import pandas as pd # Create DatetimeIndex with period 6 and frequency as D (daily) # The timezone is Australia/Sydney datetimeindex = pd.date_range('2021-10-20 02:30:50', periods=6, tz='Australia/Sydney', freq='D') # Display DateTimeIndex print("DateTimeIndex...") print(datetimeindex) ...
Read MorePython Pandas - Extract the quarter of the date from the DateTimeIndex with specific time series frequency
To extract the quarter of the date from the DateTimeIndex with specific time series frequency, use the DateTimeIndex.quarter property. Syntax DateTimeIndex.quarter This property returns an Int64Index containing the quarter of each date in the DateTimeIndex. Quarter Mapping The quarters are mapped as follows ? Quarter 1 = January to March Quarter 2 = April to June Quarter 3 = July to September Quarter 4 = October to December Creating a DateTimeIndex First, let's create a DateTimeIndex with specific frequency ? import pandas as pd # ...
Read MorePython Pandas - Extract the day of week from the DateTimeIndex with specific time series frequency
To extract the day of week from a DateTimeIndex with specific time series frequency, use the DateTimeIndex.dayofweek property. This property returns integers from 0-6 representing Monday through Sunday. Creating a DateTimeIndex with Frequency First, let's create a DateTimeIndex with a specific frequency using pd.date_range() ? import pandas as pd # Create DatetimeIndex with period 6 and frequency 3D (every 3 days) datetimeindex = pd.date_range('2021-10-20 02:30:50', periods=6, tz='Australia/Sydney', freq='3D') print("DateTimeIndex...") print(datetimeindex) DateTimeIndex... DatetimeIndex(['2021-10-20 02:30:50+11:00', '2021-10-23 02:30:50+11:00', '2021-10-26 ...
Read MorePython Pandas - Extract the ordinal day of year from the DateTimeIndex with specific time series frequency
To extract the ordinal day of year from the DateTimeIndex with specific time series frequency, use the DateTimeIndex.dayofyear property. The ordinal day of year represents which day of the year it is (1-365 or 1-366 for leap years). Creating DateTimeIndex with Time Series Frequency First, let's create a DateTimeIndex with daily frequency and extract the day of year ? import pandas as pd # Create DatetimeIndex with period 6 and frequency as D (daily) # The timezone is Australia/Sydney datetimeindex = pd.date_range('2021-10-20 02:30:50', periods=6, tz='Australia/Sydney', freq='D') # Display DateTimeIndex print("DateTimeIndex...") print(datetimeindex) # Display ...
Read MorePython Pandas - Return numpy array of python datetime.time objects
To return numpy array of python datetime.time objects, use the datetimeindex.time property in Pandas. This property extracts only the time component from datetime objects, discarding date and timezone information. Syntax DatetimeIndex.time This property returns a numpy array containing datetime.time objects. Creating a DatetimeIndex First, let's create a DatetimeIndex with timezone information ? import pandas as pd # Create DatetimeIndex with nanosecond frequency datetimeindex = pd.date_range('2021-10-20 02:30:50', periods=3, tz='Australia/Sydney', freq='ns') print("DateTimeIndex...") print(datetimeindex) DateTimeIndex... DatetimeIndex(['2021-10-20 02:30:50+11:00', ...
Read MorePython Pandas - Extract the nanoseconds from the DateTimeIndex with specific time series frequency
To extract the nanoseconds from the DateTimeIndex with specific time series frequency, use the DateTimeIndex.nanosecond property. This property returns an Int64Index containing the nanosecond values for each datetime in the index. Syntax DateTimeIndex.nanosecond Creating DateTimeIndex with Nanosecond Frequency First, let's create a DateTimeIndex with nanosecond frequency to demonstrate the nanosecond extraction ? import pandas as pd # Create DatetimeIndex with period 6 and frequency as ns (nanoseconds) # The timezone is Australia/Sydney datetimeindex = pd.date_range('2021-10-20 02:30:50', periods=6, tz='Australia/Sydney', freq='ns') # Display DateTimeIndex print("DateTimeIndex...", datetimeindex) DateTimeIndex... DatetimeIndex(['2021-10-20 ...
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