在 pandas Z23EEEB4347BDD26BFC6B7 中使用 dataframe.loc 將數據插入 dataframe 中的特定位置

Question

我嘗試使用兩個選項將數據插入 dataframe 中的特定位置。 Option 1 uses fixed colum label and variable index label and Option 2 uses fixed index label and variable colum label and then Option 1 has no error but Option 2 has warning PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`

選項 1：無警告

import pandas as pd

df=pd.DataFrame()

for col in range(200):
    df.loc[str(col),'A']=str(col)

選項 2：警告

df1=pd.DataFrame()
for col in range(200):
    df1.loc['A',str(col)]=str(col)

Answer 1

Pandas 實際上並不是為了在循環中重復添加/插入數據而設計的。 這會產生許多昂貴的中間體。

而是使用低級別的 object（列表/字典）循環，最后構造 DataFrame一次。

第一個代碼：

df = pd.DataFrame({'A': {str(i):i for i in range(200)}})

第二個代碼：

df = pd.DataFrame.from_dict({'A': {str(i):i for i in range(200)}}, orient='index')