[英]find first non-null & non-empty string value
I was using this to find the first non null value of a string:我用它来查找字符串的第一个非空值:
def get_first_non_null_values(df):
first_non_null_values = []
try:
kst = df['kst'].loc[df['kst'].first_valid_index()]
first_non_null_values.append(kst)
except:
kst = df['kst22'].loc[df['kst22'].first_valid_index()]
first_non_null_values.append(kst)
return first_non_null_values
first_non_null_values = get_first_non_null_values(df_merged)
This worked but now in my new dataset, I have some null values and some ""
empty strings.这有效,但现在在我的新数据集中,我有一些空值和一些""
空字符串。 How can I modify this such that I can extract the first value which is neither null not an empty string如何修改它,以便我可以提取第一个值,它既不是 null 也不是空字符串
You can use a combination of notnull
/ astype(bool)
and idxmax
:您可以使用notnull
/ astype(bool)
和idxmax
:
(df['col'].notnull()&df['col'].astype(bool)).idxmax()
Example input:示例输入:
>>> df = pd.DataFrame({'col': ['', float('nan'), False, None, 0, 'A', 3]})
>>> df
col
0
1 NaN
2 False
3 None
4 0
5 A
6 3
output: 5
输出: 5
null and truthy states: null 和 truthy 状态:
col notnull astype(bool) both
0 True False False
1 NaN False True False
2 False True False False
3 None False False False
4 0 True False False
5 A True True True
6 3 True True True
If you're only interesting in strings that are not empty:如果您只对非空字符串感兴趣:
df['col'].str.len().gt(0).idxmax()
I think u need:我认为你需要:
df = pd.DataFrame({'col': ['', np.nan, '', 1, 2, 3]})
print(df['col'].loc[df['col'].replace('', np.nan).first_valid_index()])
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