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Pandas - 2.2
- pd.Series()
- pd.DataFrame()
- pd.read_pickle()
- pd.read_table()
- pd.read_csv()
- pd.read_fwf()
- pd.read_clipboard()
- pd.read_excel()
- pd.ExcelFile.parse()
- pd.read_json()
- pd.json_normalize()
- pd.read_html()
- pd.read_xml()
- pd.read_hdf()
- pd.read_feather()
- pd.read_parquet()
- pd.read_orc()
- pd.read_sql_table()
- pd.read_sql_query()
- pd.read_sql()
Creation | pd.read_clipboard()
It is built on top of pd.read_csv() method.
Method:
pd.read_clipboard(sep='\s+', dtype_backend=<no_default>, **kwargs)
Reads a table of fixed-width formatted lines into DataFrame.
Returns:
pandas.core.frame.DataFrame
Parameters:
sep: str, Optional-
Delimiter for separating data; default is whitespace ('\s+').
import pandas as pd
import pyperclip
# Data to be copied to clipboard
data = """ID\tName\tAge
1\tAlice\t25
2\tBob\t30
3\tCharlie\t35
"""
# Copy the data to the clipboard
pyperclip.copy(data)
# Read the data from the clipboard using pandas
df = pd.read_clipboard(sep='\t')
# Print the DataFrame
print(df)
'''
Output:
ID Name Age
0 1 Alice 25
1 2 Bob 30
2 3 Charlie 35
'''dtype_backend: None, Optional-
The dtype_backend parameter is new in Pandas 2.0 which is used to specify the backend for handling the types of data when reading a file.
**kwargs Optional-
This parameter allows you to pass additional keyword arguments that are forwarded to the underlying pd.read_csv method.
import pandas as pd
import pyperclip
# Data to be copied to clipboard
data = """IDabcNameabcAge
1abcAliceabc25
2abcBobabc30
3abcCharlieabc35
"""
# Copy the data to the clipboard
pyperclip.copy(data)
# Read the data from the clipboard using pandas
df = pd.read_clipboard(sep='abc', index_col='ID')
# Print the DataFrame
print(df)
'''
Output:
Name Age
ID
1 Alice 25
2 Bob 30
3 Charlie 35
'''