#53 Pandas (Part 30): Window and window functions in Python: Cumulative, Rolling | Tutorial
2.9 هزار بار بازدید -
4 سال پیش
-
The video discusses windows and
The video discusses windows and window functions in Pandas Python.
Timeline & Data
(Python 3.7)
00:00 - Welcome
00:09 - Outline of video
00:37 - What is a window and window function?
03:08 - Open Jupyter notebook
03:15 - Data
04:18 - Cumulative sum: .cumsum()
05:02 - Cumulative product: .cumprod()
05:32 - Cumulative min: .cummin()
06:09 - Cumulative max: .cummax()
06:47 - Rolling sum: .rolling().sum()
08:15 - Rolling count: .rolling().count()
09:53 - Rolling min: .rolling().min()
11:09 - Rolling max: .rolling().max()
11:44 - Rolling std: .rolling().mean()
12:42 - Rolling std: .rolling().std()
14:07 - Rolling var: .rolling().var()
15:03 - Create a DataFrame with a skewed data
16:18 - Create plots of skewed data
17:42 - Rolling skew: .rolling().skew()
18:57 - Rolling kurtosis: .rolling().kurt()
19:22 - Rolling quantile: .rolling().quantile()
20:33 - Rolling covariance: .rolling().cov()
22:27 - Rolling correlation: .rolling().corr()
23:35 - Rolling covariance: .rolling().cov()
23:57 - Rolling correlation: .rolling().corr()
24:19 - Ending notes
############
Data
############
df = pd.DataFrame({
'a':[1,2,3,4,5,6,7,8,9,10],
'b':[10,np.nan,np.nan,20,np.nan,np.nan,30, 30,30,np.nan]
})
############
#################
Descriptive Statistics
mentioned at 03:50
#################
Descriptive Statistics
Timeline & Data
(Python 3.7)
00:00 - Welcome
00:09 - Outline of video
00:37 - What is a window and window function?
03:08 - Open Jupyter notebook
03:15 - Data
04:18 - Cumulative sum: .cumsum()
05:02 - Cumulative product: .cumprod()
05:32 - Cumulative min: .cummin()
06:09 - Cumulative max: .cummax()
06:47 - Rolling sum: .rolling().sum()
08:15 - Rolling count: .rolling().count()
09:53 - Rolling min: .rolling().min()
11:09 - Rolling max: .rolling().max()
11:44 - Rolling std: .rolling().mean()
12:42 - Rolling std: .rolling().std()
14:07 - Rolling var: .rolling().var()
15:03 - Create a DataFrame with a skewed data
16:18 - Create plots of skewed data
17:42 - Rolling skew: .rolling().skew()
18:57 - Rolling kurtosis: .rolling().kurt()
19:22 - Rolling quantile: .rolling().quantile()
20:33 - Rolling covariance: .rolling().cov()
22:27 - Rolling correlation: .rolling().corr()
23:35 - Rolling covariance: .rolling().cov()
23:57 - Rolling correlation: .rolling().corr()
24:19 - Ending notes
############
Data
############
df = pd.DataFrame({
'a':[1,2,3,4,5,6,7,8,9,10],
'b':[10,np.nan,np.nan,20,np.nan,np.nan,30, 30,30,np.nan]
})
############
#################
Descriptive Statistics
mentioned at 03:50
#################
Descriptive Statistics
4 سال پیش
در تاریخ 1399/03/28 منتشر شده
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