问题:从第2行读取文件或跳过标题行

如何跳过标题行并开始从第2行读取文件?

How can I skip the header row and start reading a file from line2?


回答 0

with open(fname) as f:
    next(f)
    for line in f:
        #do something
with open(fname) as f:
    next(f)
    for line in f:
        #do something

回答 1

f = open(fname,'r')
lines = f.readlines()[1:]
f.close()
f = open(fname,'r')
lines = f.readlines()[1:]
f.close()

回答 2

如果要第一行,然后要对文件执行一些操作,此代码将很有帮助。

with open(filename , 'r') as f:
    first_line = f.readline()
    for line in f:
            # Perform some operations

If you want the first line and then you want to perform some operation on file this code will helpful.

with open(filename , 'r') as f:
    first_line = f.readline()
    for line in f:
            # Perform some operations

回答 3

如果切片可以在迭代器上工作…

from itertools import islice
with open(fname) as f:
    for line in islice(f, 1, None):
        pass

If slicing could work on iterators…

from itertools import islice
with open(fname) as f:
    for line in islice(f, 1, None):
        pass

回答 4

f = open(fname).readlines()
firstLine = f.pop(0) #removes the first line
for line in f:
    ...
f = open(fname).readlines()
firstLine = f.pop(0) #removes the first line
for line in f:
    ...

回答 5

为了概括读取多个标题行的任务并提高可读性,我将使用方法提取。假设您想标记化前三行coordinates.txt以用作标题信息。

coordinates.txt
---------------
Name,Longitude,Latitude,Elevation, Comments
String, Decimal Deg., Decimal Deg., Meters, String
Euler's Town,7.58857,47.559537,0, "Blah"
Faneuil Hall,-71.054773,42.360217,0
Yellowstone National Park,-110.588455,44.427963,0

然后提取方法允许你指定什么,你想用头信息做(在这个例子中,我们简单的记号化基础上,逗号标题行并返回一个列表,但有足够的空间做更多的工作)。

def __readheader(filehandle, numberheaderlines=1):
    """Reads the specified number of lines and returns the comma-delimited 
    strings on each line as a list"""
    for _ in range(numberheaderlines):
        yield map(str.strip, filehandle.readline().strip().split(','))

with open('coordinates.txt', 'r') as rh:
    # Single header line
    #print next(__readheader(rh))

    # Multiple header lines
    for headerline in __readheader(rh, numberheaderlines=2):
        print headerline  # Or do other stuff with headerline tokens

输出量

['Name', 'Longitude', 'Latitude', 'Elevation', 'Comments']
['String', 'Decimal Deg.', 'Decimal Deg.', 'Meters', 'String']

如果coordinates.txt包含另一个标题行,只需更改numberheaderlines。最重要的是,很清楚__readheader(rh, numberheaderlines=2)正在做什么,并且我们避免了必须弄清楚或评论为什么接受的答案的作者next()在其代码中使用原因的含糊之处。

To generalize the task of reading multiple header lines and to improve readability I’d use method extraction. Suppose you wanted to tokenize the first three lines of coordinates.txt to use as header information.

Example

coordinates.txt
---------------
Name,Longitude,Latitude,Elevation, Comments
String, Decimal Deg., Decimal Deg., Meters, String
Euler's Town,7.58857,47.559537,0, "Blah"
Faneuil Hall,-71.054773,42.360217,0
Yellowstone National Park,-110.588455,44.427963,0

Then method extraction allows you to specify what you want to do with the header information (in this example we simply tokenize the header lines based on the comma and return it as a list but there’s room to do much more).

def __readheader(filehandle, numberheaderlines=1):
    """Reads the specified number of lines and returns the comma-delimited 
    strings on each line as a list"""
    for _ in range(numberheaderlines):
        yield map(str.strip, filehandle.readline().strip().split(','))

with open('coordinates.txt', 'r') as rh:
    # Single header line
    #print next(__readheader(rh))

    # Multiple header lines
    for headerline in __readheader(rh, numberheaderlines=2):
        print headerline  # Or do other stuff with headerline tokens

Output

['Name', 'Longitude', 'Latitude', 'Elevation', 'Comments']
['String', 'Decimal Deg.', 'Decimal Deg.', 'Meters', 'String']

If coordinates.txt contains another headerline, simply change numberheaderlines. Best of all, it’s clear what __readheader(rh, numberheaderlines=2) is doing and we avoid the ambiguity of having to figure out or comment on why author of the the accepted answer uses next() in his code.


回答 6

如果您想从第2行开始读取多个CSV文件,这就像一个超级按钮

for files in csv_file_list:
        with open(files, 'r') as r: 
            next(r)                  #skip headers             
            rr = csv.reader(r)
            for row in rr:
                #do something

(这是帕菲特对另一个问题的回答的一部分)

If you want to read multiple CSV files starting from line 2, this works like a charm

for files in csv_file_list:
        with open(files, 'r') as r: 
            next(r)                  #skip headers             
            rr = csv.reader(r)
            for row in rr:
                #do something

(this is part of Parfait’s answer to a different question)


回答 7

# Open a connection to the file
with open('world_dev_ind.csv') as file:

    # Skip the column names
    file.readline()

    # Initialize an empty dictionary: counts_dict
    counts_dict = {}

    # Process only the first 1000 rows
    for j in range(0, 1000):

        # Split the current line into a list: line
        line = file.readline().split(',')

        # Get the value for the first column: first_col
        first_col = line[0]

        # If the column value is in the dict, increment its value
        if first_col in counts_dict.keys():
            counts_dict[first_col] += 1

        # Else, add to the dict and set value to 1
        else:
            counts_dict[first_col] = 1

# Print the resulting dictionary
print(counts_dict)
# Open a connection to the file
with open('world_dev_ind.csv') as file:

    # Skip the column names
    file.readline()

    # Initialize an empty dictionary: counts_dict
    counts_dict = {}

    # Process only the first 1000 rows
    for j in range(0, 1000):

        # Split the current line into a list: line
        line = file.readline().split(',')

        # Get the value for the first column: first_col
        first_col = line[0]

        # If the column value is in the dict, increment its value
        if first_col in counts_dict.keys():
            counts_dict[first_col] += 1

        # Else, add to the dict and set value to 1
        else:
            counts_dict[first_col] = 1

# Print the resulting dictionary
print(counts_dict)

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