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#32 Pandas: Missing values - 5: replace() - 18 | Tutorial
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The video discusses replace() to handle missing values in Python.
Timeline & Data
(Python 3.7)
00:00 - Welcome
00:07 - Outline of video
00:21 - Open Jupyter notebook
00:28 - Data
00:53 - replace(): Series
01:32 - replace(): list ——— list
02:09 - replace(): one dictionary ——— key:value
02:39 - replace(): DataFrame
02:54 - replace(): one dictionary ———multiple key:value pairs
04:00 - replace(): DataFrame
04:50 - replace(): list ——— value
04:59 - replace() and regex: regex ——— value
05:48 - replace(): list ——— list
06:48 - replace() and regex: list of regex ——— list of regex
08:06 - replace(): dictionary of values ——— dictionary of values
08:57 - replace() and regex: dictionary of regex ——— dictionary of values
10:17 - replace() and regex: list of regex ——— values
12:20 - replace(): number ——— value
13:05 - replace(): list of numbers ——— value
13:35 - replace and regex: (alternative usage or syntax)
13:56 - Ending notes
#############
# Data
#############
a = pd.Series([11,22,33,44])
a
dfr = pd.DataFrame({
'A': [11,22,33,44,55],
'B':['m','*','*','**','n'],
})
dfr
#############
Timeline & Data
(Python 3.7)
00:00 - Welcome
00:07 - Outline of video
00:21 - Open Jupyter notebook
00:28 - Data
00:53 - replace(): Series
01:32 - replace(): list ——— list
02:09 - replace(): one dictionary ——— key:value
02:39 - replace(): DataFrame
02:54 - replace(): one dictionary ———multiple key:value pairs
04:00 - replace(): DataFrame
04:50 - replace(): list ——— value
04:59 - replace() and regex: regex ——— value
05:48 - replace(): list ——— list
06:48 - replace() and regex: list of regex ——— list of regex
08:06 - replace(): dictionary of values ——— dictionary of values
08:57 - replace() and regex: dictionary of regex ——— dictionary of values
10:17 - replace() and regex: list of regex ——— values
12:20 - replace(): number ——— value
13:05 - replace(): list of numbers ——— value
13:35 - replace and regex: (alternative usage or syntax)
13:56 - Ending notes
#############
# Data
#############
a = pd.Series([11,22,33,44])
a
dfr = pd.DataFrame({
'A': [11,22,33,44,55],
'B':['m','*','*','**','n'],
})
dfr
#############
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