[英]Pandas: Counting empty values in columns
I have a pandas dataframe containing some info about purchases.我有一个 pandas dataframe 包含一些有关购买的信息。 It includes columns like "purchaseID", "purchaseDate", and "purchaseAmount".
它包括“purchaseID”、“purchaseDate”和“purchaseAmount”等列。 I want to know the number of missing values in each column, and different columns contain different types of datatypes like strings, numeric, booleans, etc. I tried something like this:
我想知道每列中缺失值的数量,不同的列包含不同类型的数据类型,如字符串、数字、布尔值等。我尝试过这样的事情:
import json
import pandas
# the variable 'data' is my pandas data frame which was read from a json
with open('purchases.json') as f:
data = pd.DataFrame(json.loads(line) for line in f)
print(data.isnull().sum())
print(data.isna().sum())
However, both isnull and isna are showing that there are no null values in any columns, which is not the case.但是,isnull 和 isna 都显示在任何列中都没有 null 值,但事实并非如此。
When I tried something like this:当我尝试这样的事情时:
for col in data.columns:
print((data[col].values == '').sum())
it works for some columns but not for columns that contain numeric or boolean data.它适用于某些列,但不适用于包含数字或 boolean 数据的列。 Is there a way for me to find the empty values in all the columns?
有没有办法让我在所有列中找到空值?
Thanks!谢谢!
Example printout using print of couple lines of data使用打印几行数据的示例打印输出
purchaseID purchaseDate purchaseAmount merchantName
1234 2019-01-01 500.0 Walmart
2345 2019-01-03
2019-01-02 25.1 BP
Try using pd.read_json
.尝试使用
pd.read_json
。 The problem could be your data frame with one row being the json file.问题可能是您的数据框,其中一行是 json 文件。
data = pd.read_json(r'purchases.json')
print(data.isnull().sum())
print(data.isna().sum().sum())
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