![Python如何讀取excel檔(.xlsx)?如何用欄標籤提取某一直行?df=pandas.read_excel() ; df["欄標籤"] - 儲蓄保險王](https://savingking.com.tw/wp-content/uploads/2022/05/20220512092421_65.png){kind=small}
import pandas as pd
f3 = r”C:\Python\example\csvreader\skl_cashFlowIRR2.xlsx”
df3 = pd.read_excel(f3) ;
print( df3,”\n”,type(df3) ) #DataFrame
print( df3[“Cash Flow 1″],”\n”,type(df3[“Cash Flow 1”])) #Series
print( list(df3[“Cash Flow 1”]) )
#取得到這個list,
#就可以用numpy_financial.irr()計算內部報酬率
![Python如何讀取excel檔(.xlsx)?如何用欄標籤提取某一直行?df=pandas.read_excel() ; df["欄標籤"] - 儲蓄保險王](https://savingking.com.tw/wp-content/uploads/2022/11/20221109163631_39.png)
輸出:
![Python如何讀取excel檔(.xlsx)?如何用欄標籤提取某一直行?df=pandas.read_excel() ; df["欄標籤"] - 儲蓄保險王](https://savingking.com.tw/wp-content/uploads/2022/11/20221109163816_19.png)
![Python如何做excel的樞紐分析? groupbyObj = df.groupby([‘A’, ‘B’]) ; groupbyObj.apply() 跟 groupbyObj.agg() 差異為何? result = groupbyObj .apply( function(df) -> Series ) ; result_agg = groupbyObj .agg( [‘mean’, ‘std’] ) ; aggfunc(Series) -> float](https://i1.wp.com/savingking.com.tw/wp-content/uploads/2023/03/20230327140158_46.png?quality=90&zoom=2&ssl=1&resize=350%2C233 "Python如何做excel的樞紐分析? groupbyObj = df.groupby([‘A’, ‘B’]) ; groupbyObj.apply() 跟 groupbyObj.agg() 差異為何? result = groupbyObj .apply( function(df) -> Series ) ; result_agg = groupbyObj .agg( [‘mean’, ‘std’] ) ; aggfunc(Series) -> float")
![Python: pandas.Series如何只保留str,去除重複值？#isinstance(x:Any, str) -> bool #.drop_duplicates() #Series.apply( function )逐元素應用function運算 #DataFrame.apply( function )逐Series應用function運算 .drop_duplicates() 跟.unique()有何差別? df.drop_duplicates() 等效於 df[~df.duplicated()]](https://i2.wp.com/savingking.com.tw/wp-content/uploads/2024/11/20241123194900_0_5218de.png?quality=90&zoom=2&ssl=1&resize=350%2C233 "Python: pandas.Series如何只保留str,去除重複值？#isinstance(x:Any, str) -> bool #.drop_duplicates() #Series.apply( function )逐元素應用function運算 #DataFrame.apply( function )逐Series應用function運算 .drop_duplicates() 跟.unique()有何差別? df.drop_duplicates() 等效於 df[~df.duplicated()]")
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