如何在Pandas中串联数据框

Question

I have weather data about Min and Max temperatures and Precipitation of various weather stations over a period of 1985-2014. I have found the average Min and Max temperatures for each year using GroupBy in Pandas.

data1= data
#Replaceing missing values represented by -9999 with 0
df2=data1.replace(to_replace=-9999,value=0)
#performing groupby over the year part of the string given in Date
df3=data1.groupby(df2.Date.str[0:4])
tmp=df3['MaxTemp'].mean().to_frame()

 Date MaxTemp 1985 153.347945 1986 126.963370 .... ...... 

fileName=filePath.split('\\')[-1]
#filename is USC00110072.txt

fname=pd.DataFrame([fileName]*len(tmp.index))
fname.columns=['File']
# mtemp=pd.concat([])
fname.index=[i for i in range(1985,2015)]
fname

Now I want to concatenate tmp and fname dataframes to give me data as such:

FileName Year MaxTemp USC00110072.txt 1985 153.347945205 USC00110072.txt 1986 126.963369963 .... ... ......

To do this I used pandas.concat([fname,tmp], axis=1) but I am getting following output:

              File      MaxTemp
1985    USC00110072.txt   NaN
1986    USC00110072.txt   NaN
1987    USC00110072.txt   NaN
....     ........         ...
1985       NaN          153.347945
1986       NaN          126.963370
1987       NaN          177.602740

Please suggest what changes should I make in the concat function so that I get the desired output.

Answer 1

Problem is in first dataframes years are strings, in second integers.

So need convert string s to integer s by astype :

tmp = (data.replace(to_replace=-9999,value=0)
           .groupby(data.Date.str[0:4].astype(int))
           .mean()
           .to_frame())

Also solution should be simplify by assign for append new column with same values:

df = (data.replace(to_replace=-9999,value=0)
          .groupby(data.Date.str[0:4].astype(int))
          .mean()
          .to_frame()
          .assign(File = fileName))