Pandas frequency

All frequency offset in pandas

Alias    Description
B        business day frequency
C        custom business day frequency
D        calendar day frequency
W        weekly frequency
M        month end frequency
SM       semi-month end frequency (15th and end of month)
BM       business month end frequency
CBM      custom business month end frequency
MS       month start frequency
SMS      semi-month start frequency (1st and 15th)
BMS      business month start frequency
CBMS     custom business month start frequency
Q        quarter end frequency
BQ       business quarter end frequency
QS       quarter start frequency
BQS      business quarter start frequency
A, Y     year end frequency
BA, BY   business year end frequency
AS, YS   year start frequency
BAS, BYS business year start frequency
BH       business hour frequency
H        hourly frequency
T, min   minutely frequency
S        secondly frequency
L, ms    milliseconds
U, us    microseconds
N        nanoseconds

Source: stackoverflow.com

Change the frequency to column in pandas

print df['status'].value_counts()
N    14
S     4
C     2
Name: status, dtype: int64

counts = df['status'].value_counts().to_dict()
print counts
{'S': 4, 'C': 2, 'N': 14}

Source: stackoverflow.com

Data series to datetime

pd.to_datetime(your_series)

Pandas frequency

# # frequancy calculation. Es. vogliamo sapere la frequenza dei paesi per continente
# print(df.groupby('continent')['country'].nunique())

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