我有兩個不同的功能，有兩個不同的字典。首先，我必須將字典合并為一個，然后連接兩個資料框。
import pandas as pd
output_df1 = {}
output_df1['diff_sum'] = 108
output_df1['cumsum'] = 232
out2 = {}
out2['carving'] = 1299
out2['bearing'] = 255
merge_dict = {**output_df1, **out2}
# upto this I'm able to do this
new_df = pd.DataFrame()
new_df['tata'] = merge_dict
new_df['diff_sum'] = 108
new_df
得到結果
想要這個
我該怎么做？
uj5u.com熱心網友回復：
您也可以merge_dict通過將索引名稱設定為'tata'然后轉置來直接將其轉換為資料框。
df2 = pd.DataFrame(merge_dict, index=['tata']).T
In [27]: df2
Out[27]:
tata
diff_sum 108
cumsum 232
carving 1299
bearing 255
uj5u.com熱心網友回復：
嘗試：
new_df = pd.DataFrame(merge_dict.values(), index=merge_dict, columns=["tata"])
print(new_df)
印刷：
tata
diff_sum 108
cumsum 232
carving 1299
bearing 255
uj5u.com熱心網友回復：
這對我有用：
import pandas as pd
output_df1 = {}
output_df1['diff_sum'] = 108
output_df1['cumsum'] = 232
out2 = {}
out2['carving'] = 1299
out2['bearing'] = 255
merge_dict = {**output_df1, **out2}
# upto this I'm able to do this
new_df = pd.DataFrame(merge_dict.values(),index=merge_dict.keys(),columns=['tata'])
new_df
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