Pandas dropna 在特定行上

Question

import pandas as pd
df = pd.DataFrame({'ticker':['x','x','y','z','z'],
                   'bid':[1,2,np.nan,2,np.nan]})

Using pandas .dropna() is there anyway to drop the rows from a specified index range or subset of the data? For example in the DataFrame above, if I want to only drop rows in the index for where ticker equals 'z' . This would hopefully return:

ticker bid
x       1
x       2
y       np.nan
z       2

Answer 1

One option is to just check the two conditions separately:

In [13]: df[(df['bid'].notnull()) | (df['ticker'] != 'z')]
Out[13]:

---

  ticker  bid
0      x  1.0
1      x  2.0
2      y  NaN
3      z  2.0

Answer 2

df.loc[df.ticker == "z"] = df.loc[df.ticker == "z"].dropna()
df.dropna(subset=["ticker"])

Not sure if this is better for when I have more columns and need to specify if they have 2 missing nan's (using the .dropna(thresh=2) in the first drop)

Answer 3

You can use dropna with mask and fillna :

df.mask(df.eq('z')).dropna(how='all').fillna({'ticker':'z'})

Output:

 ticker  bid
0      x  1.0
1      x  2.0
2      y  NaN
3      z  2.0

or

df.mask(df.eq('z')).dropna(how='all').mask(df.eq('z'),'z')