series

问题 For a given series, e.g. s = pd.Series([0,0,0]) I would like to check whether ALL elements in this series are equal to a specific value (we can use 0 in this example) and return TRUE if that is the case, and FALSE otherwise. is there a handy way to do those in Pandas/numpy? 回答1: You should use the following syntax: s = pd.Series([0,0,0]) print(s.eq(0).all()) True 回答2: Another way to do the same would be: print((s==0).all()) 来源： https://stackoverflow.com/questions/58359706/how-to-check-whether

问题 For a given series, e.g. s = pd.Series([0,0,0]) I would like to check whether ALL elements in this series are equal to a specific value (we can use 0 in this example) and return TRUE if that is the case, and FALSE otherwise. is there a handy way to do those in Pandas/numpy? 回答1: You should use the following syntax: s = pd.Series([0,0,0]) print(s.eq(0).all()) True 回答2: Another way to do the same would be: print((s==0).all()) 来源： https://stackoverflow.com/questions/58359706/how-to-check-whether

问题 All, To replace one string in one particular column I have done this and it worked fine: dataUS['sec_type'].str.strip().str.replace("LOCAL","CORP") I would like now to replace multiple strings with one string say replace ["LOCAL", "FOREIGN", "HELLO"] with "CORP" How can make it work? the code below didnt work dataUS['sec_type'].str.strip().str.replace(["LOCAL", "FOREIGN", "HELLO"], "CORP") 回答1: You can perform this task by forming a |-separated string. This works because pd.Series.str.replace

问题 All, To replace one string in one particular column I have done this and it worked fine: dataUS['sec_type'].str.strip().str.replace("LOCAL","CORP") I would like now to replace multiple strings with one string say replace ["LOCAL", "FOREIGN", "HELLO"] with "CORP" How can make it work? the code below didnt work dataUS['sec_type'].str.strip().str.replace(["LOCAL", "FOREIGN", "HELLO"], "CORP") 回答1: You can perform this task by forming a |-separated string. This works because pd.Series.str.replace

问题 All, To replace one string in one particular column I have done this and it worked fine: dataUS['sec_type'].str.strip().str.replace("LOCAL","CORP") I would like now to replace multiple strings with one string say replace ["LOCAL", "FOREIGN", "HELLO"] with "CORP" How can make it work? the code below didnt work dataUS['sec_type'].str.strip().str.replace(["LOCAL", "FOREIGN", "HELLO"], "CORP") 回答1: You can perform this task by forming a |-separated string. This works because pd.Series.str.replace

问题 I'm trying to approximate e^x using the Maclaurin series in a function called my_exp(x) , I believe everything I've done so far is right but I'm getting incorrect approximations for whatever number I try. import math for i in range (x): exp = 1 + ((x**i)/math.factorial(i)) print(exp) For example, whenever I try my_exp(12) I get 18614.926233766233 instead of 162754.79141900392 Help? 回答1: Your problem is that the e^x series is an infinite series, and so it makes no sense to only sum the first x

问题 I'm trying to approximate e^x using the Maclaurin series in a function called my_exp(x) , I believe everything I've done so far is right but I'm getting incorrect approximations for whatever number I try. import math for i in range (x): exp = 1 + ((x**i)/math.factorial(i)) print(exp) For example, whenever I try my_exp(12) I get 18614.926233766233 instead of 162754.79141900392 Help? 回答1: Your problem is that the e^x series is an infinite series, and so it makes no sense to only sum the first x

问题 I am trying to sort a Pandas Series in ascending order. Top15['HighRenew'].sort_values(ascending=True) Gives me: Country China 1 Russian Federation 1 Canada 1 Germany 1 Italy 1 Spain 1 Brazil 1 South Korea 2.27935 Iran 5.70772 Japan 10.2328 United Kingdom 10.6005 United States 11.571 Australia 11.8108 India 14.9691 France 17.0203 Name: HighRenew, dtype: object The values are in ascending order . However, when I then modify the series in the context of the dataframe : Top15['HighRenew'] =

问题 I'm trying to get the index of 6th item in the Series I have. This is how the head looks like United States 1.536434e+13 China 6.348609e+12 Japan 5.542208e+12 Germany 3.493025e+12 France 2.681725e+12 For getting the 6th index name ( 6th Country after being sorted ), I usually use s.head(6) and get the 6th index from there s.head(6) gives me United States 1.536434e+13 China 6.348609e+12 Japan 5.542208e+12 Germany 3.493025e+12 France 2.681725e+12 United Kingdom 2.487907e+12 and looking at this,

问题 Hope you could help me. I am new to python and pandas, so please bear with me. I am trying to find the common word between three data frames and I am using Jupiter Notebook. Just for example: df1= A dog cat cow duck snake df2= A pig snail bird dog df3= A eagle dog snail monkey There is only one column in all data frames that is A. I would like to find the common word among all columns the words that are unique to their own columns and not in common. Example: duck is unique to df1, snail is