如何从列表创建单个列的DataFrame，其中第一个元素是python中的列名

Question

I have the below data in a csv and I am trying to create a dataframe of 1 column by selecting each column from the csv at a time.

sv_m1   rev     ioip    
0       15.31   40      
0       64.9    0       
0       18.36   20      
0       62.85   0       
0       10.31   20      
0       12.84   10      
0       69.95   0       
0       32.81   20  

The list that I get, the first value is the column name and remaining are values.

input_file = open('df_seg_sample.csv', 'r')
c_reader = csv.reader(input_file, delimiter=',')
#Read column
column = [x[1] for x in c_reader]
label = column[0]
column = column[1:]
df_column = pd.DataFrame.from_records(data = column,columns = label)

However this gives me an error:

  TypeError: Index(...) must be called with a collection of some kind, 'sv_m1' was passed

core is actually the column name.

How can I create this df? The column name of the df will be the first element in the list and all other items in the list will be the column values.

The reason for not using pandas.read_csv is: The dataframe is huge and hogs up a lot of memory. So I want to read in a column at a time, do some processing and write it to another csv.

Answer 1

I think need read_csv here with usecols parameter for filter second column:

df = pd.read_csv('df_seg_sample.csv', usecols=[1])
print (df)
     rev
0  15.31
1  64.90
2  18.36
3  62.85
4  10.31
5  12.84
6  69.95
7  32.81

But if want use your solution is necssary add [] for one item list for column name and use only DataFrame contructor:

data = [x[1] for x in c_reader]
print (data)
['rev', '15.31', '64.9', '18.36', '62.85', '10.31', '12.84', '69.95', '32.81']

df = pd.DataFrame(data[1:], columns=[data[0]])
print (df)
     rev
0  15.31
1   64.9
2  18.36
3  62.85
4  10.31
5  12.84
6  69.95
7  32.81