CODEWITHSUNDEEP
pythonpandasdataframe
Horacio Nesman
Horacio Nesman

Reputation: 111

efficient way to convert str to integers

I have a data frame that looks like this:

Index([u'Date', u'Time', u'Hi Temperature', u'Low Temperature', u'HIT?', u'LOT?', u'Date+Time'], dtype='object')

I created the columns 'HIT?', 'LOT?' and 'Date+Time'

I am trying to create a list of 'Date+Time' in which a certain condition is verified, e.g.: 

data2['HIT?'] is 'TRUE' OR data2['LOT?'] = 'TRUE'.

I run the script 

Hi_Low = []
for i in data2['Date+Time']:
    if (data2[data2['Date+Time']==map(str,i)['HIT?']] == True) or (data2[data2['Date+Time']==map(str,i)]['LOT?']== True):
        Hi_Low.append(i)
    else:
        pass

but got the error:

TypeError: list indices must be integers, not str

I thought that the function map would convert the indices, but is not doing it, anybody can give me hand with this?? or any other way to approach this problem?

Upvotes: 1

Views: 57

Answers (1)

jezrael
jezrael

Reputation: 863791

I think you need boolean indexing with loc for filtering only column Date+Time:

df = pd.DataFrame({'HIT?':[True, False, True, False],
                   'LOT?':[True, True, False, False],
                   'Date+Time':pd.date_range('2017-01-01 13:49:02', periods=4),
                   'Hi Temperature':[10,40,50,60],
                   'Low Temperature':[2,5,7,8]})
print (df)
  Date+Time   HIT?  Hi Temperature   LOT?  Low Temperature
0 2017-01-01   True              10   True                2
1 2017-01-02  False              40   True                5
2 2017-01-03   True              50  False                7
3 2017-01-04  False              60  False                8

Hi_Low = df.loc[df['HIT?'] | df['LOT?'], 'Date+Time'].tolist() 
print (Hi_Low)
[Timestamp('2017-01-01 13:49:02'), 
 Timestamp('2017-01-02 13:49:02'), 
 Timestamp('2017-01-03 13:49:02')]

Hi_Low = df.loc[df['HIT?'] | df['LOT?'], 'Date+Time'].astype(str).tolist() 
print (Hi_Low)
['2017-01-01 13:49:02', '2017-01-02 13:49:02', '2017-01-03 13:49:02']

It is same as:

Hi_Low = df.loc[(df['HIT?'] == True) | 
                (df['LOT?'] == True), 'Date+Time'].astype(str).tolist() 
print (Hi_Low)
['2017-01-01 13:49:02', '2017-01-02 13:49:02', '2017-01-03 13:49:02']

Also is possible use conditions with chaining by | (or), & (and) or ~ (not):

Hi_Low = df.loc[(df['Hi Temperature'] > 45) | 
                (df['Low Temperature'] < 5), 'Date+Time'].astype(str).tolist() 
print (Hi_Low)
['2017-01-01 13:49:02', '2017-01-03 13:49:02', '2017-01-04 13:49:02']

Upvotes: 1

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