Mapping Data Frame Values to Dictionary Is Not Working-CodePudding

I have this dataframe (dd) like this

|Month||Price|
1   55.96
6   381.16
7   825.80

I want to replace the value of the month in each row with the related month. I created a dictionary

R={'January': 1,'June': 6,'July': 7,'August': 8,'September': 9,'October': 10,'November': 11,'December': 12}

and then I used this in an attempt to do the replacements

dd['Month']=dd["Month"].map(R)

but when I print out my data frame I get this as an output:

Month Price
NaN   55.96
NaN   381.16
NaN   825.80

I'm not sure why I am getting NaN. Clearly something is happening but I have no idea what, why, and how to fix it.

I am new to python so still figuring out my way. My formatting in this q is probably a dead giveaway lol. Please dumb down your explanations :)

CodePudding user response：

Your mapping dictionary is set up the wrong way. You need to reverse key-value pairs:

reverse_R = {v:k for k,v in R.items()}
df['Month'] = df['Month'].map(reverse_R)

Output:

     Month   Price
0  January   55.96
1     June  381.16
2     July  825.80

CodePudding user response：

Try flipping your dictionary around so that the key is the integer and the value contains the month as a string.

R = {1:'January', 6:'June', 7:'July', 8:'August', 9:'September', 10: 'October', 11: 'November', 12:'December'

The map method maps keys to values. Your dictionary was just reversed.

Furthermore, according to the documentation if a value is missing the map function will return a NaN.

CodePudding user response：

Because your month dictionary key and values are vice versa , it should be like this :

R={1:'January',6:'June',7:'July'}

then it works :

dd['Month']=dd["Month"].map(R)

output> 

     month   Price
0  January   55.96
1     June  381.16
2     July  825.80