Question

我在行“ added_parts = new_part_set [（new_part_set [“ duplicate”] == False）＆（new_part_set [“ version”] ==“ target”）]“ **下得到E712的薄片8错误。 / p>

以下是我们用于电子表格比较的代码段

source_df = pd.read_excel(self.source, sheet).fillna('NA')
target_df = pd.read_excel(self.target, sheet).fillna('NA')
file_path = os.path.dirname(self.source)

column_list = source_df.columns.tolist()

source_df['version'] = "source"
target_df['version'] = "target"

source_df.sort_values(by=unique_col)
source_df = source_df.reindex()
target_df.sort_values(by=unique_col)
target_df = target_df.reindex()

# full_set = pd.concat([source_df, target_df], ignore_index=True)
diff_panel = pd.concat([source_df, target_df],
                       axis='columns', keys=['df1', 'df2'], join='outer', sort=False)
diff_output = diff_panel.apply(self.__report_diff, axis=0)
diff_output['has_change'] = diff_output.apply(self.__has_change)

full_set = pd.concat([source_df, target_df], ignore_index=True)
changes = full_set.drop_duplicates(subset=column_list, keep='last')
dupe_records = changes.set_index(unique_col).index.unique()

changes['duplicate'] = changes[unique_col].isin(dupe_records)
removed_parts = changes[(changes["duplicate"] == False) & (changes["version"] == "source")]
new_part_set = full_set.drop_duplicates(subset=column_list, keep='last')
new_part_set['duplicate'] = new_part_set[unique_col].isin(dupe_records)
added_parts = new_part_set[(new_part_set["duplicate"] == False) & (new_part_set["version"] == "target")]

diff_file = file_path + "file_diff.xlsx"
if os.path.exists(diff_file):
    os.remove(diff_file)
writer = pd.ExcelWriter(file_path + "file_diff.xlsx")
diff_output.to_excel(writer, "changed")
removed_parts.to_excel(writer, "removed", index=False, columns=column_list)
added_parts.to_excel(writer, "added", index=False, columns=column_list)
writer.save()

还有其他方法可以避免这种情况吗？不确定是否继续进行。

Answer 1

在DataFrame掩码中，您有172.19.0.2:8080 172.19.0.3:8080和server server-a server-a:8080 check server server-b server-b:8080 check flake8建议您更改这些掩码。它抱怨的原因是在python中，使用(changes["duplicate"] == False)运算符与布尔值进行比较被认为是不好的做法，而应该编写(new_part_set["duplicate"] == False)和==等。在熊猫中，如果您具有布尔值系列，您可以使用if my_bool:...运算符取反，这样就可以编写新的蒙版了：

if not my_bool:...

如何修复plates 8错误pandas dataframe中的“ E712与False的比较应该是'如果cond为False：'或'如果不是cond：'”

1 个答案: