问题
I have a df like this,
case step deep value
0 case 1 1 ram in India ram,cricket
1 NaN 2 ram plays cricket NaN
2 case 2 1 ravi played football ravi
3 NaN 2 ravi works welll NaN
4 case 3 1 Sri bought a car sri
5 NaN 2 sri went out NaN
and a dictionary, my_dict = {ram:1,cricket:1,ravi:2.5,sri:1}
I am trying to re-order the dataframe according to the values of the dictionary, I achieved this dictionary using tfidf method. I face difficulty in re-ordering as we need to re-order the rows including with the values.
My expected output is,
case step deep value
2 case 2 1 ravi played football ravi
3 NaN 2 ravi works welll NaN
0 case 1 1 ram in India ram,cricket
1 NaN 2 ram plays cricket NaN
4 case 3 1 Sri bought a car sri
5 NaN 2 sri went out NaN
Please help, thanks in advance!
回答1:
You can create MultiIndex for sorting, only is necessary values from column value are in my_dict:
my_dict = {'ram':1,'cricket':1,'ravi':2.5,'sri':1}
#create DataFrame from value column, replace and sum columns
a = df['value'].str.split(',', expand=True).replace(my_dict).sum(axis=1)
#create groups
b = df['step'].diff().le(0).cumsum()
#create Series by summing per groups
c = a.groupby(b).transform('sum')
#create MultiIndex
df.index = [c,b]
print (df)
case step deep value
step
2.0 0 case 1 1 ram in India ram,cricket
0 NaN 2 ram plays cricket NaN
2.5 1 case 2 1 ravi played football ravi
1 NaN 2 ravi works welll NaN
1.0 2 case 3 1 Sri bought a car sri
2 NaN 2 sri went out NaN
#sorting MultiIndex and removing
df = df.sort_index(ascending=False).reset_index(drop=True)
print (df)
case step deep value
0 case 2 1 ravi played football ravi
1 NaN 2 ravi works welll NaN
2 case 1 1 ram in India ram,cricket
3 NaN 2 ram plays cricket NaN
4 case 3 1 Sri bought a car sri
5 NaN 2 sri went out NaN
来源：https://stackoverflow.com/questions/48860471/how-to-re-order-a-pandas-dataframe-based-on-a-dictionary-condition