python access specific value in a pandas dataframe
pandas dataframe get cell value by condition
pandas get row by index
pandas get cell value without index
'dataframe' object has no attribute 'get_value'
pandas set value
I'm just starting up with python and am struggling to extract a value from my first column, at the end of the dataframe.
so let's say I have a .csv file with 3 columns:
id,name,country 1,bob,USA 2,john,Brazil 3,brian,austria
i'm trying to extract '3' from the ID column (last row ID value)
fileName=open('data.csv') reader=csv.reader(fileName,delimiter=',') count=0 for row in reader: count=count+1
I'm able to get the rowcount, but am unsure how to get the value from that particular column
this should do the job:
import csv fileName=open('123.csv') reader=csv.reader(fileName,delimiter=',') count=0 for row in reader: if count == 3: print(row) count=count+1
but its better to import pandas and convert your csv file to a dataframe by doing this :
import csv import pandas as pd fileName=open('123.csv') reader=csv.reader(fileName,delimiter=',') df = pd.DataFrame(reader) print(df.loc)
it would be easier to grab whatever element you want.
loc, you can access any element using the row number and the column number, for example you wanted to grab the element 3 which is on the row 3, column 0, so you just grab it by
if you don't have pandas installed, install it in the command prompt using the command:
pip install pandas
Python, Pandas dataframe.get_value() function is used to quickly retrieve single value in the data frame at passed column and index. The input to the function is the row Just for reference, here is how the complete dataframe looks like: And before extracting data from the dataframe, it would be a good practice to assign a column with unique values as the index of the dataframe. The State column would be a good choice. Assigning an index column to pandas dataframe ¶ df2 = df1.set_index("State", drop = False)
I found your question a bit ambiguous, so I'm answering for both cases.
If you need the first column, third row value:
value = None with open('data.csv') as fileName: reader = csv.reader(fileName, delimiter=',') for row_number, row in enumerate(reader, 1): if row_number == 3: value = row
If you need the first column, last row value:
value = None with open('data.csv') as fileName: reader = csv.reader(fileName, delimiter=',') for row in reader: value = row
In both cases,
value has the value you want.
pandas.DataFrame.at, Access a single value for a row/column label pair. Similar to loc , in that both provide label-based lookups. Use at if you only need to get I have imported the data in csv format in pandas. Can anybody tell me how i can find the values above 280 in one of the columns that i have and put them into another data frame. I have done the below code so far: import numpy as np import pandas as pd df = pd.read_csv('csv') And the part of data is like the attached pic:enter image
As mentioned in the comments
df['id'].iloc[-1] will return the last id value in the DataFrame which in this case is what you want.
You can also access based on the values in the other rows. For example:
df.id[(df.name == 'brian')] would also give you a value of 3 because brian is the name associated with an id of 3.
You also don't have to loop through the DataFrame rows to get the size, but when you have the DataFrame loaded can simply do
count = df.shape which will return the number of rows.
Accessing pandas dataframe columns, rows, and cells, Accessing pandas dataframe columns, rows, and cells data from the dataframe, it would be a good practice to assign a column with unique values as the index of the dataframe. Extracting specific columns of a pandas dataframe ¶. Pandas dataframe.get_value() function is used to quickly retrieve single value in the data frame at passed column and index. The input to the function is the row label and the column label. Syntax: DataFrame.get_value(index, col, takeable=False) Parameters : index : row label col : column label takeable : interpret the index/col as indexers, default False
Given that you are starting with Python, and looking at the code provided, I think this Idiomatic Python video will be super helpful. Transforming Code Into Beautiful, Idiomatic Python | Raymond Hettinger
In addition to pandas documentation referenced below, this summary is pretty helpful as well: Select rows in pandas MultiIndex DataFrame.
Pandas indexing documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html
Pandas how to get a cell value and update it, at - Access a single value for a row/column label pair Use at if you only Pandas xs Extract a particular cross section from a Series/DataFrame. at – Access a single value for a row/column label pair. Use at if you only need to get or set a single value in a DataFrame or Series. Let’s create a Dataframe first. import pandas as pddf = pd.DataFrame([[30, 20, 'Hello'], [None, 50, 'foo'], [10, 30, 'poo']], columns=['A', 'B', 'C'])df. 1.
How to get a value from a cell of a Pandas DataFrame, iloc to get value from a cell of a Pandas Dataframe; iat and at to get value from a cell of a Pandas pythonCopy # python 3.x import pandas as pd df = pd. And loc gets rows (or columns) with particular labels from the index. For pandas 0.10, where iloc is unavalable, filter a DF and get the first row data for the column VALUE: df_filt = df[df['C1'] == C1val & df['C2'] == C2val] result = df_filt.get_value(df_filt.index,'VALUE') if there is more then 1 row filtered, obtain the first row value. There will be an exception if the filter result in empty data frame.
Pandas Indexing Examples: Accessing and Setting Values on , Some common ways to access rows in a pandas dataframe, includes Use .loc[<label_values>] to select rows based on their string labels:. import numpy as np import pandas as pd df = pd.DataFrame(np.random.rand(100, 100)) %timeit df.iat[50,50]=50 # %timeit df.at[50,50]=50 # %timeit df.set_value(50,50,50) # will deprecate %timeit df.iloc[50,50]=50 %timeit df.loc[50,50]=50 7.06 µs ± 118 ns per loop (mean ± std. dev. of 7 runs, 100000 loops each) 5.52 µs ± 64.2 ns per loop (mean
Indexing, Slicing and Subsetting DataFrames in Python – Data , How can I access specific data within my data set? How can Python and Pandas help me to analyse my data? Objectives. Describe what 0-based indexing is. Reassign values within subsets of a DataFrame. Create a copy of a DataFrame. Use the values attribute to return the values as a np array and then use  to get the first value: In : df.loc[df.Letters=='C','Letters'].values Out: 'C' EDIT
- post as answer i'll mark it completed @QuangHoang
- i'm looking for this to be dynamic. I need to grab the last value in that column
- check out pandas, it has what exactly what you want, in my answer I wrote a simple implementation but you should have pandas to run it.