pandas将df赋值到另一个df_为pandasdf添加标签，然后将df连接到另一个df现在标签是一个列表给出了什么？...

我有两个需要连接的csv文件。我在两个csv文件中读取了pandas dfs。一个有col标签&＃xff0c;另一个没有。我将标签添加到需要它们的df&＃xff0c;然后连接两个dfs。连接工作正常&＃xff0c;但我添加的标签看起来像个别列表或其他东西。我无法弄清楚python正在做什么&＃xff0c;特别是当你打印标签和df时&＃xff0c;它看起来都很好。称之为这种方法。

我能够通过在读取csv时将col标签添加到csv来解决问题。然后它工作正常。称这种方法为二。方法一是怎么回事&＃xff1f;

以下代码和结果。

接近一个

#read in the vectors as a pandas df vec

vecs&＃61;pd.read_csv(os.path.join(path,filename), header&＃61;None)

#label the feature vectors v1-vn and attach to the df

endrange&＃61;features&＃43;1

string&＃61;&＃39;v&＃39;

vecnames&＃61;[string &＃43; str(i) for i in range(1,endrange)]

vecs.columns &＃61; [vecnames]

print(&＃39;\nvecnames&＃39;)

display(vecnames) #they look ok here

display(vecs.head()) #they look ok here

#read in the IDs and phrases as a pandas df

recipes&＃61;pd.read_csv(os.path.join(path,&＃39;2a_2d_id_all_recipe_forms.csv&＃39;))

print(&＃39;\nrecipes file - ids and recipe phrases&＃39;)

display(recipes.head())

test&＃61;pd.concat([recipes, vecs], axis&＃61;1)

print(&＃39;\ncol labels for vectors look like lists!&＃39;)

display(test.head())

方法一的结果&＃xff1a;

[&＃39;v1&＃39;,

&＃39;v2&＃39;,

&＃39;v3&＃39;,

&＃39;v4&＃39;,

&＃39;v5&＃39;,

&＃39;v6&＃39;,

&＃39;v7&＃39;,

&＃39;v8&＃39;,

&＃39;v9&＃39;,

&＃39;v10&＃39;,

&＃39;v11&＃39;,

&＃39;v12&＃39;,

&＃39;v13&＃39;,

&＃39;v14&＃39;,

&＃39;v15&＃39;,

&＃39;v16&＃39;,

&＃39;v17&＃39;,

&＃39;v18&＃39;,

&＃39;v19&＃39;,

&＃39;v20&＃39;,

&＃39;v21&＃39;,

&＃39;v22&＃39;,

&＃39;v23&＃39;,

&＃39;v24&＃39;,

&＃39;v25&＃39;]

接近两个

当我读取未标记的文件时&＃xff0c;通过将col标签添加到csv&＃xff0c;它可以正常工作。为什么呢&＃xff1f;

#label the feature vectors v1-vn and attach to the df

endrange&＃61;features&＃43;1

string&＃61;&＃39;v&＃39;

vecnames&＃61;[string &＃43; str(i) for i in range(1,endrange)]

#read in the vectors as a pandas df and label the cols

vecs&＃61;pd.read_csv(os.path.join(path,filename), names&＃61;vecnames, header&＃61;None)

#read in the IDs and phrases as a pandas df

recipes&＃61;pd.read_csv(os.path.join(path,&＃39;2a_2d_id_all_recipe_forms.csv&＃39;))

test&＃61;pd.concat([recipes, vecs], axis&＃61;1)

print(&＃39;\ncol labels for vectors as expected&＃39;)

display(test.head())

方法二的结果