Python: printing strings and data frames

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I am trying to create a report using python to populate the data. Below is an example. I have used pandas to read the csv to create the data frame. I then have to use the cells to populate the text.

Dataframe:

    name    age
0   Chris   15
1   Kim     20
2   David   18

How do I get python to print the following:

name is Chris age 15.
name is Kim age 20.
name is David age 18.

Code:

import pandas
data = pandas.DataFrame({'name': ['Chris', 'Kim', 'David'],
                         'age': [15, 20, 18]})

for index, row in data.iterrows():
  print('name is {} age {}.'.format(row['name'], row['age']))

Output:

name is Chris age 15.
name is Kim age 20.
name is David age 18.

If a list of strings is given, it is assumed to be aliases for the column names. index​bool, optional, default True. Whether to print index (row) labels. na_repstr,  Python | Pandas DataFrame.to_string Pandas DataFrame is a two-dimensional size-mutable, potentially heterogeneous tabular data structure with labeled axes (rows and columns). Arithmetic operations align on both row and column labels.

Use lambda to iterate over

import pandas
data = pandas.DataFrame({'name': ['Chris', 'Kim', 'David'],
                         'age': [15, 20, 18]})
def print_func(x):
    print('name is {} and age is {}'.format(x['name'],x['age']))

data.apply(lambda x:print_func(x),axis=1)

Output:

name is Chris and age is 15
name is Kim and age is 20
name is David and age is 18

Next, create the DataFrame to capture the above data in Python. DataFrame(​Data) df['Price'] = df['Price'].apply(str) print (df) print (df.dtypes). Python comes with a built-in function for accepting input from the user, predictably called input (). It accepts data from the standard input stream, which is usually the keyboard: >>>. >>> name = input('Enter your name: ') Enter your name: jdoe >>> print(name) jdoe.

In [12]: import pandas as pd

In [13]: df = pd.DataFrame([
    ...:     {'name': 'Chris', 'age': 15},
    ...:     {'name': 'Kim', 'age': 20},
    ...:     {'name': 'David', 'age': 18}
    ...: ])

In [14]: df
Out[14]: 
   age   name
0   15  Chris
1   20    Kim
2   18  David

In [15]: for name, age in zip(df['name'], df['age']):
    ...:     # Python 3.6+ 
    ...:     print(f'name is {name} age {age}')
    ...:
    ...:     # Python 3.5 and below
    ...:     # print('name is {name} age {age}'.format(**df.to_dict()))
    ...:     
name is Chris age 15
name is Kim age 20
name is David age 18

In [16]: 

Series and Indexes are equipped with a set of string processing methods that make As shown in the output image of data frame, all values in the Team column  Print very long string completely in pandas dataframe. Asked 4 years, 7 months ago. Active 3 days ago. Viewed 69k times. I am struggling with the seemingly very simple thing.I have a pandas data frame containing very long string. df = pd.DataFrame( {'one' : ['one', 'two', 'This is very long string very long string very long string veryvery long

We have some data present in string format, discuss ways to load that data into pandas df = pd.read_csv(StringData, sep = ";" ). # Print the dataframe. print (df) the column type from string to datetime format in Pandas dataframe · Python  Once you have data in Python, you’ll want to see the data has loaded, and confirm that the expected columns and rows are present. Print the data. If you’re using a Jupyter notebook, outputs from simply typing in the name of the data frame will result in nicely formatted outputs.

Almost, all of these methods work with Python string functions (refer: Returns the DataFrame with One-Hot Encoded values. 8. contains(pattern) Series(['Tom ', ' William Rick', 'John', 'Alber@t']) print s print ("Split Pattern:") print s.str.split(' '). Normal strings in Python are stored internally as 8-bit ASCII, while Unicode strings are stored as 16-bit Unicode. This allows for a more varied set of characters, including special characters from most languages in the world. I'll restrict my treatment of Unicode strings to the following −. Live Demo.

How to create a Pandas DataFrame from a string in Python. Creating a Pandas df = pd.read_csv(data, sep=","). create DataFrame from `data`. print(df). Output. Strings are Arrays. Like many other popular programming languages, strings in Python are arrays of bytes representing unicode characters. However, Python does not have a character data type, a single character is simply a string with a length of 1. Square brackets can be used to access elements of the string. Example.