Python Fundamentals (Part 4.)

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)