02/19 - 02/24
Missing Values
isnull(); isna(); notnull()
df.dropna()
default axis =0
default how = "any" , which means that if any row contain any NaN, that row will be dropped!
if how="all", rows that include NaN in every column will be dropped
df.fillna()
duplicated()
Notes: duplicated(keep='first')
default setting is keep = 'first'
duplicated(keep='last')
duplicated(keep=False)
df.drop_duplicates
pd.Series
df.groupby()
/////// df.groupby() & dictionary
pd.MultiIndex.from_arrays()
df.groupby(level, ...)
# set_index()
# resample()
# pd.Grouper()
Note: 'MS' means 'beginning of the month'
df.agg()
pd.merge()
Notes:
in df1, subject_id: sub1,sub2,sub4,sub6,sub5
in df2, subject_id: sub2, sub4, sub3,sub6,sub5
pd.concat()
df.plot(); plt.show()
Notes:
plt.subplot(num_rows, num_cols, plot_num)
