如何使用Pandas将文本文件的列转换为单行CSV文件？

I see you're trying to convert a text file with variable-length rows into two single-line CSV entries, ordered column-wise. Your initial code ran into issues because zip() stops at the shortest line, and you referenced undefined columns. Let's fix this with Pandas, which handles variable-length data nicely.

Step-by-Step Solution: #

1. Read and Split Input Lines: First, we read the text file and split each line into individual elements.
2. Split into Groups: Separate the data string lines and number lines into two distinct groups.
3. Process Each Group with Pandas:
   • Convert each group into a DataFrame (Pandas will automatically fill missing values with NaN for shorter rows).
   • Iterate over each column, collect non-null values, and concatenate them in column-wise order.
   • Join the collected values into a comma-separated string.
4. Write to CSV: Save the two processed lines into your output CSV file.

Full Code: #

import pandas as pd

# Read the input text file
with open("file.txt", "r") as f:
    # Split each line into elements, skipping any empty lines
    lines = [line.strip().split() for line in f if line.strip()]

# Split into data group (first 4 lines) and number group (next 4 lines)
data_group = lines[:4]
num_group = lines[4:]

# Process the data string group
df_data = pd.DataFrame(data_group)
data_result = []
for col in df_data.columns:
    # Collect non-null values from each column
    data_result.extend(df_data[col].dropna().tolist())
data_line = ','.join(data_result)

# Process the number group
df_num = pd.DataFrame(num_group)
num_result = []
for col in df_num.columns:
    # Convert numbers to strings and collect non-null values
    num_result.extend(df_num[col].dropna().astype(str).tolist())
num_line = ','.join(num_result)

# Write the result to CSV
with open("file.csv", "w") as fout:
    fout.write(f"{data_line}\n")
    fout.write(f"{num_line}\n")

How This Works: #

• DataFrame Handling: When we create a DataFrame from variable-length rows, Pandas fills missing positions with NaN, which makes it easy to filter out empty entries later.
• Column-Wise Collection: By iterating over each column and collecting non-null values, we ensure we follow the exact order you want: all first-column elements, then all second-column elements, and so on.
• String Conversion: For the number group, we convert values to strings to ensure they join correctly into a CSV line.

This will produce the exact output you described, with each group's elements ordered column-wise in a single CSV line.

内容的提问来源于stack exchange，提问作者Sandeep Singh