code: df = [
'Timestamp;T;Pressure [bar];Input line pressure [bar];Speed [rpm];Angular Position [degree];Wheel speed [rpm];Wheel angular position [degree];',
';1;5,281;5,303;219,727;10,283;216,363;45;',
';1;5,273;5,277;219,727;11,602;216,363;45;',
';1;5,288;5,293;205,078;12,832;216,363;45;',
';1;5,316;5,297;219,727;14,15;216,363;45;',
';1;5,314;5,307;219,727;15,469;216,363;45;',
';1;5,288;5,3;219,727;16,787;216,363;45;',
';1;5,318000000000001;5,31;219,727;18,105;216,363;45;',
';1;5,304;5,3;219,727;19,424;216,388;56,25;',
';1;5,291;5,29;219,947;20,742;216,388;56,25;',
';1;5,316;5,297;219,507;22,061;216,388;56,25;']
mat = [n.split(';') for n in df]
print(mat)
newdf1 = pd.DataFrame(mat)
newdf1.columns = newdf1.iloc[0]
newdf1 = newdf1.reindex(newdf1.index.drop(0))
# newdf2 = pd.DataFrame.from_dict(df)
print(newdf1)
output: 0 Timestamp T Pressure [bar] Input line pressure [bar] Speed [rpm] \
1 1 5,281 5,303 219,727
2 1 5,273 5,277 219,727
3 1 5,288 5,293 205,078
4 1 5,316 5,297 219,727
5 1 5,314 5,307 219,727
6 1 5,288 5,3 219,727
7 1 5,318000000000001 5,31 219,727
8 1 5,304 5,3 219,727
9 1 5,291 5,29 219,947
10 1 5,316 5,297 219,507
0 Angular Position [degree] Wheel speed [rpm] \
1 10,283 216,363
2 11,602 216,363
3 12,832 216,363
4 14,15 216,363
5 15,469 216,363
6 16,787 216,363
7 18,105 216,363
8 19,424 216,388
9 20,742 216,388
10 22,061 216,388
0 Wheel angular position [degree]
1 45
2 45
3 45
4 45
5 45
6 45
7 45
8 56,25
9 56,25
10 56,25
- HowTo
- Python Pandas Howtos
- Load Data From Text File in Pandas
Created: March-19, 2020 | Updated: December-10, 2020
read_csv() Method to Load Data From Text Fileread_fwf() Method to Load Width-Formated Text File to Pandas DataFrame read_table() Method to Load Text File to Pandas DataFrame
We will introduce the methods to load the data from a txt file with Pandas DataFrame . We will also go through the available options.
First, we will create a simple text file called sample.txt and add
the following lines to the file: 45 apple orange banana mango
12 orange kiwi onion tomato
We need to save it to the same directory from where Python script will be running. read_csv() Method to Load Data From Text Fileread_csv() is the best way to convert the text file into Pandas DataFrame . We need to set header=None as we don’t have any header in the above-created file. We can
also set keep_default_na=False inside the method if we wish to replace empty values with NaN .
Example Codes: # python 3.x
import pandas as pd
df = pd.read_csv(
'sample.txt', sep=" ",header=None)
print(df)
Output: 0 1 2 3 4
0 45 apple orange banana mango
1 12 orange kiwi onion tomato
We set sep=" " because a single white space separates values. Similarly, we can set sep="," if we read data from a comma-separated file. Replace the white spaces inside sample.txt with , and then run the code after replacing sep=" " with sep="," . Sample.txt 45,apple,orange,banana,mango
12,orange,kiwi,,tomato
Code: # python 3.x
import pandas as pd
df = pd.read_csv(
'sample.txt', sep=",",header=None)
print(df)
Output: 0 1 2 3 4
0 45 apple orange banana mango
1 12 orange kiwi NaN tomato
read_fwf() Method to Load Width-Formated Text File to Pandas DataFrameread_fwf() is very helpful to load a width-formatted text file. We can’t use sep because different values may have different delimiters. Consider the following text file:
Sample.txt 45 apple orange banana mango
12 orange kiwi onion tomato
In Sample.text , delimiter is not the same for all values. So read_fwf() will do the job here. Code: # python 3.x
import pandas as pd
df = pd.read_fwf(
'sample.txt',header=None)
print(df)
Output:
0 1 2 3 4
0 45 apple orange banana mango
1 12 orange kiwi onion tomato
read_table() Method to Load Text File to Pandas DataFrameread_table() is another approach to load data from text file to Pandas DataFrame .
Sample.txt: 45 apple orange banana mango
12 orange kiwi onion tomato
Code: # python 3.x
import pandas as pd
df = pd.read_table(
'sample.txt',header=None,sep=" ")
print(df)
Output: 0 1 2 3 4
0 45 apple orange banana mango
1 12 orange kiwi onion tomato
How do I import a text file into a DataFrame?
Method 1: Using read_csv(). filename. txt: As the name suggests it is the name of the text file from which we want to read data.. sep: It is a separator field. ... . header: This is an optional field. ... . names: We can assign column names while importing the text file by using the names argument..
What are the ways to store text data in pandas?
There are two ways to store text data in pandas: object -dtype NumPy array. StringDtype extension type.. You can accidentally store a mixture of strings and non-strings in an object dtype array. ... . object dtype breaks dtype-specific operations like DataFrame..
How do I rename a column in DF?
One way of renaming the columns in a Pandas Dataframe is by using the rename() function. This method is quite useful when we need to rename some selected columns because we need to specify information only for the columns which are to be renamed.
What is the use of To_string in Python?
Render a DataFrame to a console-friendly tabular output. Buffer to write to. If None, the output is returned as a string.
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