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A free scan shows the junk files, broken settings and background clutter dragging Windows down - then fixes them in one click.Free scan · Windows 10 & 11For a DataFrame already loaded in Python, use df = df.set_index(df.columns[0]). To set the first column as the index while loading a CSV, use pd.read_csv("data.csv", index_col=0). The first approach uses the column’s position regardless of its name; the second applies that choice during import.
Set the first column as the index in an existing DataFrame
Use DataFrame.set_index with the label of the first column, which you can get by position from df.columns:
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df = df.set_index(df.columns[0])This returns a DataFrame with the selected column used for row labels. By default, drop=True, so that column is removed from the ordinary data columns. Assign the result back to df; otherwise, the original DataFrame remains unchanged.
Keep the source column in the data
To use the first column as the index and also retain it as a regular column, set drop=False:
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df = df.set_index(df.columns[0], drop=False)Use a column name when it is known
If the column is specifically named id, naming it directly makes the code independent of column order:
df = df.set_index("id")You can also pass inplace=True to modify the existing DataFrame, but that call returns None; do not assign its result back to df.
Set the first column as the index when reading a CSV
Pass the zero-based column position 0 as index_col to pandas.read_csv:
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df = pd.read_csv("data.csv", index_col=0)This reads the CSV and uses its first column as the index, without first loading that column as ordinary data and then converting it.
If a malformed CSV has extra delimiters at the ends of lines and you do not want pandas to treat the first column as the index, the read_csv documentation describes index_col=False for that case.
Use more than one column for the index
If rows are identified by a combination of the first two columns, pass both positions. This creates a MultiIndex, so use it only when the combination reflects the row labels you intend:
# Existing DataFrame
df = df.set_index([df.columns[0], df.columns[1]])
# CSV import
df = pd.read_csv("data.csv", index_col=[0, 1])set_index also accepts column names or a list of keys. See the pandas indexing guide for the broader method overview.
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Importing from Excel
read_excel accepts index_col, including a zero-based column position. However, pandas documents that missing values in an index column may be forward-filled to support round-tripping files with merged cells. If that fill would alter values you need to preserve, read the sheet first and then call set_index. The pandas I/O guide covers CSV and Excel behavior.
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