Removing index column in pandas when reading a csv
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I have the following code which imports a CSV file. There are 3 columns and I want to set the first two of them to variables. When I set the second column to the variable "efficiency" the index column is also tacked on. How can I get rid of the index column?
df = pd.DataFrame.from_csv('Efficiency_Data.csv', header=0, parse_dates=False) energy = df.index efficiency = df.Efficiency print efficiency
I tried using
after I set
energy = df.index
which I found in another post but that results in "KeyError: 'index' "
DataFrames and Series always have an index. Although it displays alongside the column(s), it is not a column, which is why
del df['index'] did not work.
If you want to replace the index with simple sequential numbers, use
To get a sense for why the index is there and how it is used, see e.g. 10 minutes to Pandas.
How to avoid Python/Pandas creating an index in a saved csv , above problem would be, you can save your dataframe as it is with an index, and while reading the columns you just need to drop the column As others have stated, if you don't want to save the index column in the first place, you can use df.to_csv('processed.csv', index=False). However, since the data you will usually use, have some sort of index themselves, let's say a 'timestamp' column, I would keep the index and load the data using it.
When reading to and from your CSV file include the argument
index=False so for example:
and to read from the csv
This should prevent the issue so you don't need to fix it later.
Removing index column in pandas when reading a csv , Removing index column in pandas when reading a csv. I have the following code which imports a CSV file. There are 3 columns and I want to set the first two of when writing file you can use the following code if you don't want pandas to write the index column in the csv file. pd.to_csv('your.csv', index=False) Also if you want to drop the index when reading a file you should be able to do it through: df = pd.read_csv('some.csv').drop(['Unnamed 0'],axis=1)
pandas.read_csv, read_csv; read_excel; read_hdf; read_sql; read_json; read_msgpack i.e. from StringIO import StringIO for Python 2 and from io import StringIO for Python 3. a list of integers that specify row locations for a multi-index on the columns E.g. [0,1,3]. By default the parser removes the component date columns, but you can Pandas consist of read_csv function which is used to read the required CSV file and usecols is used to get the required columns. drop. Pandas consist of drop function which is used in removing rows or columns from the CSV files. Syntax import pandas as pd temp=pd.read_csv('filename.csv') temp.drop('Column_name',axis=1,inplace=True) temp.head()
You can set one of the columns as an index in case it is an "id" for example. In this case the index column will be replaced by one of the columns you have chosen.
IO Tools (Text, CSV, HDF5, ), How do I remove an index from a column in a data frame? Stopgap Solution: Filtering with str.match. If you cannot modify the code to read/write the CSV file, you can just remove the column by filtering with str.match: Thanks a lot! That index_col= fix easily solved this annoying problem of 'unnamed:0' and spares code from verbose reinventing the wheel.
If your problem is same as mine where you just want to reset the column headers from 0 to column size. Do
df = pd.DataFrame(df.values);
Not a good idea if you have heterogenous data types. Better just use
df.columns = range(len(df.columns))
How to drop the index column of a pandas DataFrame in Python, How do I read a column from a CSV file in Python using pandas? Use index_col=False instead of index_col=None when you have delimiters at the end of each line to turn off index column inference and discard the last column. After looking at the data, there is a comma at the end of each line. And this quote (the documentation has been edited since the time this post was created):
How to set Column as Index in Pandas DataFrame? – 2 Python , Python | Pandas DataFrame. reset_index() Parameters: level: int, string or a list to select and remove passed column from index. drop: Boolean value, Adds the replaced index column to the data if False. inplace: Boolean value, make changes in the original data frame itself if True. If a column or index cannot be represented as an array of datetimes, say because of an unparseable value or a mixture of timezones, the column or index will be returned unaltered as an object data type. For non-standard datetime parsing, use pd.to_datetime after pd.read_csv.
How to read specific column from CSV file in Python, Pandas provide data analysts a way to delete and filter data frame using .drop() method. Rows or columns can be removed using index label or column name using this To download the CSV used in code, click here. import pandas as pd. Pandas Read CSV: Remove Unnamed Column. In some of the previous read_csv example, we get an unnamed column. In previous sections, of this Pandas read CSV tutorial, we have solved this by setting this column as index or used usecols to select specific columns from the CSV file. However, we may not want to do that for some reason.
Python, import pandas as pd>>> df = pandas.read_csv('data/sample.csv') It is auto-generated index column, because pandas always tries to optimize However, drop will return new modified DataFrame, so we need to store it The best way to delete a column in pandas is to use drop: where 1 is the axis number (0 for rows and 1 for columns.) To delete the column without having to reassign df you can do: Finally, to drop by column number instead of by column label, try this.
- Thanks! I decided to just import it a different way not using pandas. I have to perform some arithmetic on each of the columns and python wasn't liking have the index column attached. Pandas is certainly the easiest way to import data but not always the best I found out.
- Did you try using Pandas to do the arithmetic?
- can one remove the index name?
index.name = None.
- @BogdanJaniszewski, if you didn't use pandas, then why did you accept this as the answer?
- Thanks a lot.This is exactly what is the question is looking for.
- "header = False" works for removing headers in the same way
- should be
df.to_sql("table",cursor,if_exists="append",index=False)also fixes the sqlite error
sqlite3.OperationalError: table message has no column named index
- @vedda it seems to be
read_csv()in pandas 0.23.4. :-/
- This is actually my favorite solution, but not a very elaborate answer. The manual reads this about the argument
drop: "Do not try to insert index into dataframe columns. This resets the index to the default integer index." pandas.pydata.org/pandas-docs/stable/generated/…
- Error: "labels ['index'] not contained in axis"