我还在循环中使用了数据框的 函数，感到困惑的是它的运行速度如何。
根据此页面上的正确答案，为遭受苦难的人提供有用的示例。
Python版本：3
熊猫版：0.20.3
# the dictionary to pass to pandas dataframe
dict = {}
# a counter to use to add entries to "dict"
i = 0
# Example data to loop and append to a dataframe
data = [{"foo": "foo_val_1", "bar": "bar_val_1"},
{"foo": "foo_val_2", "bar": "bar_val_2"}]
# the loop
for entry in data:
# add a dictionary entry to the final dictionary
dict[i] = {"col_1_title": entry['foo'], "col_2_title": entry['bar']}
# increment the counter
i = i + 1
# create the dataframe using 'from_dict'
# important to set the 'orient' parameter to "index" to make the keys as rows
df = DataFrame.from_dict(dict, "index")
“ from_dict”函数：https://pandas.pydata.org/pandas- docs/stable/generation/pandas.DataFrame.from_dict.html
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