pandas 删除 NaN 行在熊猫中不起作用
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Dropping NaN rows doesn't work in pandas
提问by user3088202
I have a file with about 7k rows and 4 columns. A lot of the cells are empty and I have tried to drop them using a number of pandas functions but nothing seems to work. Functions I have tried and the code are below:
我有一个大约有 7k 行和 4 列的文件。很多单元格都是空的，我尝试使用许多 Pandas 函数删除它们，但似乎没有任何效果。我尝试过的功能和代码如下：
What I have tried:
我尝试过的：
df = df.dropna(thresh=2)
and
和
df.dropna(axis=0, how='all')
My code:
我的代码：
file = "pc-dirty-data.csv"
path = root + file
name_cols = ['GUID1', 'GUID2', 'Record ID', 'Name', 'Org Name', 'Title']
pull_cols = ['Record ID', 'Name', 'Org Name', 'Title']
df = df.dropna(thresh=2)
df.dropna(axis=0, how='all')
df = pd.read_csv(path, header=None, encoding="ISO-8859-1", names=name_cols, usecols=pull_cols, index_col=False)
df.info()
Dataframe:
数据框：
RangeIndex: 6599 entries, 0 to 6598
Data columns (total 4 columns):
Record ID 5874 non-null float64
Name 5874 non-null object
Org Name 5852 non-null object
Title 5615 non-null object
dtypes: float64(1), object(3)
回答by Scott Boston
dropnais not an inplace operation, you need to reassign it back to the variable or use the inplaceparameter set to True.
dropna不是就地操作，您需要将其重新分配回变量或使用inplace设置为 True的参数。
df = df.dropna(axis=0, how='all')
or
或者
df.dropna(axis=0, how='all', inplace=True)
Edit
编辑
Jay points out in the comments that, you need to reorder you code logic such that you dropna after the read_csv.
Jay 在评论中指出，您需要对代码逻辑重新排序，以便在 read_csv 之后删除。
