Delete and replace Nan values with mean of the rows in pandas dataframe

Question

I have a very big DataFrame that looks like:

    c1   c2    c3
0  NaN  1.0   NaN
1  NaN  NaN   NaN
2  3.0  6.0   9.0
3  NaN  7.0  10.0
...

I want to:

1- Delete the rows with all "Nan" values. like the second row in the sample.

2- Replace all the "Nan" values in other rows with the mean of the rows.

Note: in the rows, we have different "Nan" values. could you please help me with that? Thanks.

Also, this link does not solve my question: Pandas Dataframe: Replacing NaN with row average

Here is a sample of my DataFrame:

import pandas as pd
import numpy as np


df = pd.DataFrame()
df['c1'] = [np.nan, np.nan, 3, np.nan]
df['c2'] = [1, np.nan, 6, 7]
df['c3'] = [np.nan, np.nan, 9, 10]

Update: When we don't want to consider the mean of all rows. sample dataframe:

import pandas as pd
import numpy as np


df = pd.DataFrame()
df['id'] = [1, 2, 3, 4, 5]
df['c1'] = [np.nan, np.nan, 3, np.nan, 5]
df['c2'] = [1, np.nan, 3, 11, 5]
df['c3'] = [1, np.nan, 3, 11, np.nan]
df['c4'] = [3, np.nan, 3, 11, 5]

output: 
df = pd.DataFrame()
df['id'] = [1,  3, 4, 5]
df['c1'] = [ 5/3, 3, 11, 5]
df['c2'] = [1,  3, 11, 5]
df['c3'] = [1,  3, 11, 5]
df['c4'] = [3,  3, 11, 5]
df

For this part, I don't want to consider the value of id for calculating the mean of row.

Answer 1

how about this :

df = df.T.fillna(df.mean(axis=1)).T.dropna()
print(df)

output:

>>>
    c1   c2    c3
0  1.0  1.0   1.0
2  3.0  6.0   9.0
3  8.5  7.0  10.0