[FIXED] How to remove NaN from the columns

Issue

I have a dataframe with NaN. I have to remove nan at the starting rows only, and wants to keeps NaN after real number starts:

Suppose my data frame is something like:

a = pd.DataFrame({'data':[np.nan,np.nan,np.nan,np.nan,4,5,6,2,np.nan,1,3,4,5,np.nan,4,5,np.nan,np.nan]})

a= 
    data
    0   NaN
    1   NaN
    2   NaN
    3   NaN
    4   4.0
    5   5.0
    6   6.0
    7   2.0
    8   NaN
    9   1.0
    10  3.0
    11  4.0
    12  5.0
    13  NaN
    14  4.0
    15  5.0
    16  NaN
    17  NaN

and I tried to remove NaN at the beginning and wants data-frame like this:

        data
    4   4.0
    5   5.0
    6   6.0
    7   2.0
    8   NaN
    9   1.0
    10  3.0
    11  4.0
    12  5.0
    13  NaN
    14  4.0
    15  5.0
    16  NaN
    17  NaN

I tried to use this function but it is not working.

for w in np.arange(len(a)):
    if a.iloc[w] == np.nan:
        a.drop(a.index[w])

Solution

Get the first valid index and slice

idx = a.first_valid_index()
a.loc[idx:]

    data
4   4.0
5   5.0
6   6.0
7   2.0
8   NaN
9   1.0
10  3.0
11  4.0
12  5.0
13  NaN
14  4.0
15  5.0
16  NaN
17  NaN

Answered By - Vaishali