We are trying to read a sample simple csv file using pandas in python as follows -
df = pd.read_csv('example.csv')
print(df)
We need df by removing below red highlighted index column -
We have tried multiple ways by passing parameters but no luck.
Please help me in this issue!!
A dataframe requires having some kind of index as part of the structure.
If you want to simply print the output without the index you can use the approach suggested here, with Python 3 syntax:
print(df.to_string(index=False))
but it will not have the nice dataframe rendering in Jupyter as you have in your example.
If you want to avoid pandas outputting the index when writing to a CSV file you can use the option index=False, for example:
df.to_csv('example.csv', index=False)
This will avoid creating the index column in the saved CSV file.
add index_col=False
pd.read_csv('path.csv',index_col=False)
or remove index from dataframe
df.reset_index(drop=True, inplace=True)
Related
In stack, overflow I see a lot of questions about removing index from dataframes made be to_csv.
However, what I want to do is add an index to an already made csv file with no index.
Here is my file:
How do we add an index to this csv with pandas?
If you read csv file as dataframe, pandas will automatically generate index. You don't need to do something else.
So, just read it and write again as below
import pandas as pd
df = pd.read_csv("your_file.csv")
df.to_csv("your_file_to_save.csv")
please see attached photo
here's the image
I only need to import a specific column with conditions(such as specific data found in that column). And also, I only need to remove unnecessary columns. dropping them takes too much code. What specific code or syntax is applicable?
How to get a column from pandas dataframe is answered in Read specific columns from a csv file with csv module?
To quote:
Pandas is spectacular for dealing with csv files, and the following
code would be all you need to read a csv and save an entire column
into a variable:
import pandas as pd
df = pd.read_csv(csv_file)
saved_column = df.column_name #you can also use df['column_name']
So in your case, you just save the the filtered data frame in a new variable.
This means you do newdf = data.loc[...... and then use the code snippet from above to extract the column you desire, for example newdf.continent
enter image description here
Hi, I am very new to Python and I plan to create a final exportable table with these reviews scraped from a website to see the words that were most used. I have thus managed to get this 2 columns but have no idea how to proceed, can I directly export this into a table in excel or must I convert it into a dataframe then export it to a CSV? And what is the required code to run as such? Thank you so much for your help!!
It's convenient to use pandas library for working with dataframes:
import pandas as pd
series = pd.Series(wordcount)
series.to_csv("wordcount.csv")
However, if you use the code above, you'll get a warning. To fix it, there are 2 ways:
1) Add header parameter:
series.to_csv("wordcount.csv", header=True)
2) Or convert series to dataframe and then save it (without new index):
df = series.reset_index()
df.to_csv("wordcount.csv", index=False)
I have a tsv file which I am trying to read by the help of pandas. The first two rows of the files are of no use and needs to be ignored. Although, when I get the output, I get it in the form of two columns. The name of the first column is Index and the name of second column is a random row from the csv file.
import pandas as pd
data = pd.read_csv('zahlen.csv', sep='\t', skiprows=2)
Please refer to the screenshot below.
The second column name is in bold black, which is one of the row from the file. Moreover, using '\t' as delimiter does not separate the values in different column. I am using Spyder IDE for this. Am I doing something wrong here?
Try this:
data = pd.read_table('zahlen.csv', header=None, skiprows=2)
read_table() is more suited for tsv files and read_csv() is a more specialized version of it. Then header=None will make first row data, instead of header.
I want to put some data available in an excel file into a dataframe in Python.
The code I use is as below (two examples I use to read an excel file):
d=pd.ExcelFile(fileName).parse('CT_lot4_LDO_3Tbin1')
e=pandas.read_excel(fileName, sheetname='CT_lot4_LDO_3Tbin1',convert_float=True)
The problem is that the dataframe I get has the values with only two numbers after comma. In other words, excel values are like 0.123456 and I get into the dataframe values like 0.12.
A round up or something like that seems to be done, but I cannot find how to change it.
Can anyone help me?
thanks for the help !
You can try this. I used test.xlsx which has two sheets, and 'CT_lot4_LDO_3Tbin1' is the second sheet. I also set the first value as Text format in excel.
import pandas as pd
fileName = 'test.xlsx'
df = pd.read_excel(fileName,sheetname='CT_lot4_LDO_3Tbin1')
Result:
In [9]: df
Out[9]:
Test
0 0.123456
1 0.123456
2 0.132320
Without seeing the real raw data file, I think this is the best answer I can think of.
Well, when I try:
df = pd.read_csv(r'my file name')
I have something like that in df
http://imgur.com/a/Q2upp
And I cannot put .fileformat in the sentence
You might be interested in removing column datatype inference that pandas performs automatically. This is done by manually specifying the datatype for the column. Here is what you might be looking for.
Python pandas: how to specify data types when reading an Excel file?
Using pandas 0.20.1 something like this should work:
df = pd.read_csv('CT_lot4_LDO_3Tbin1.fileformat')
for exemple, in excel:
df = pd.read_csv('CT_lot4_LDO_3Tbin1.xlsx')
Read this documentation:
http://pandas.pydata.org/pandas-docs/stable/generated/pandas.read_csv.html