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Read Specific Cells (Cell by Cell) in csv File - Python Automation and Machine Learning for ICs - - An Online Book - |
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| Python Automation and Machine Learning for ICs http://www.globalsino.com/ICs/ | ||||||||
| Chapter/Index: Introduction | A | B | C | D | E | F | G | H | I | J | K | L | M | N | O | P | Q | R | S | T | U | V | W | X | Y | Z | Appendix | ||||||||
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The "nrows=1" parameter is used when reading a CSV file using the pd.read_csv function. It specifies the number of rows to read from the CSV file. In this case, "nrows=1" means that only the first row of the CSV file is being read without reading the entire file. On the other hand, after reading the first row using "nrows=1", "iat[n, m]" typically refers to accessing a specific element (n, m) in a DataFrame using the ".iat" accessor. Specifically, "iat" is used for fast scalar access by integer position. For instance, the "[1, 1]" case would mean retrieving the element at the second row and second column (zero-indexed) of the DataFrame. Similarly, "iat[1, 0]" refers to the element at the second row and first column of the DataFrame. It is used to extract the value in the second cell of the first row. The code is essentially reading specific cells from the CSV file without loading the entire dataset into memory, making it efficient for quick inspection of specific values. ============================================ Read a CSV file which has a single cell in the first rows and multiple cells in the later rows. Code: 
============================================ Drop the rows with a single column and then set a row as a new header. Code:
Input:
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