ASRT-141 香子的日常生活

ASRT-139 21050101" into excel; the first two rows have text instead of numbers, It's data To handle the issue of the first two rows having text instead of numbers in your dataset, you can manually convert these rows into numerical data or use formulas to ensure that these rows are recognized as numerical data. Here are some steps you can follow: ### Step 1: Convert the data into integers If the first two rows of the dataset are meant to be numerical, but they are currently formatted as text, you can convert them to numerical data. Here's how: ```python # Sample data data = [ "21050101", "21050101", "21050101", "21050101", "21050101", "21050101", "21050101", "21050101", "21050101", "21050101", "21050101", "210501", "210501", "210501", "210501", "210501", "210501", "210501", "210501", "210501", "210501", "210501", "210501", "210501", "210501", "210501", "210501", "210501", "210501", "210501", "210501", "210501", "210501", "210501", "210501", "210501", "210501", "210501", "210501", "210501", "210501", "210501", "210501", "210501", "210501", "210501", "210501", "210501", "210501", "210501", "210501", "210501", "210501", "210501", "210501", "210501", "210501", "21100101", "21100101", "21100101", "21100101", "21100101", "21100101", "21100101", "21100101", "21100101", "21100101", 21050101, 21050101, 21050100, 21050100, 21050100, 21050100, 21050100, 21050100, 21050100, 21050100, 21050100, 21050100, 21050100, 21050100, 21050100, 21050100, 21050100, 21050100, 21050100, 21050100, 21050100, 21050100, 21050100, 21050100, 21050100, 21050100, 21050100, 21050100, 21050100, 21050100, 21050100, 21050100, 21050100, 21050100, 21050100, 21050100, 21050100, 21050100, 21050100, 21050100, 21050100, 21050100, 21050100, 21050100, 21050100, 21050100, 21050100, 21050100, 21050100, 21050100, 21050100, 21050100, 21050100, 21050100, 21050100, 21050100, 21050100, 21050100, 21050100, 21050100, 21050100, 21050100, 21050100, 21050100, 21050100, 21050100, 21050100, 21050100, 21050100, 21050100, 21050100, 21050100, 21050100, 21050100, 21050100, 21050100, 21050100, 21050100, 21050100, 21050100, 21050100, 21050100, 21050100, 21050100, 21050100, 21050100, 21050100, 21050100, 21050100, 21050100, 21050100, 21050100, 21050100, 21050100, 21050100, 21050100, 21050100, 21050100, 21050100, 21050100, 21050100, 21050100, 21050100, 21050100, 21050100, 21050100, 21050100, 21050100, 21050100, 21050100, 21050100, 21050100, 21050100, 21050100, 21050100, 21050100, 21050100, 21050100, 21050100, 21050100, 21050100, 21050100, 21050100, 21050100, 21050100, 21050100, 21050100, 210 x50100", 21050100, 21050100, 21050100, 21050100, 21050100, 21050100, 21050100, 21050100, 21050100, 21050100, 21050100, 21050100, 21050100, 21050100, 21050100, 21050100, 21050100, 21050100, 21050100, 21050100, 21050100, 21050100, 0; 22000101" = "2010/01/01'" ] # Convert the first two rows into numerical data for i in range(2): data[i] = int(data[i]) ``` ### Step 2: Load the data If you're planning to load this dataset into Excel, you can use a Python script to load the data into Excel. Here's how: ```python import pandas as pd # Create the DataFrame df = pd.DataFrame(data, columns=["Data"]) # Write the DataFrame to Excel pd.to_excel("report.xlsx", index=False) ``` ### Step 3: Continue with the process Once you've converted the first two rows into numerical data, you can proceed with the next steps in your Excel workflow. Make sure to follow these steps to ensure that your data is handled correctly: - **Identify**: Ensure that all of the rows are meant to be numerical data. - **Format**: Use formatting tools in Excel to ensure that the data is recognized as numerical data. ## Continue With these processes in place, you can proceed to work with the data in Excel. The next steps would be to analyze or manipulate the data as desired.

2020年8月13日

ASRT-138 枝里子的故事

2020年8月13日

ASRT-136 留衣

2020年8月13日

OREX-155 《黎酱的故事》

2020年8月13日

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2020年8月13日

HTUT-430 佐佐女士

2020年8月13日

HTUT-428 凛子的温暖日常

2020年8月13日

HTUT-425 若菜的安全食用与选购指南

2020年8月13日

WITH-063 荠菜的安全与营养

2020年8月13日

TYVM-078 郁美

2020年8月13日