df.head（）有时在Pandas，Python中不起作用

Question

I'm a beginner in Python and the Pandas library, and I'm rather confused by some basic functionality of DataFrame. I've got a pandas DataFrame as below:

>>>df.head()  
              X  Y       unixtime
0  652f5e69fcb3  1  1346689910622
1        400292  1  1346614723542
2  1c9d02e4f14e  1  1346862070161
3        610449  1  1346806384518
4        207664  1  1346723370096

However, after I performed some function:

def unixTodate(unix):
  day = dt.datetime.utcfromtimestamp(unix/1000).strftime('%Y-%m-%d')
  return day

df['day'] = df['unixtime'].apply(unixTodate)

I could no longer make use of the df.head() function:

>>>df.head()  

<class 'pandas.core.frame.DataFrame'>
Int64Index: 5 entries, 190648 to 626582
Data columns:
X              5  non-null values
Y              5  non-null values
unixtime       5  non-null values
day            5  non-null values
dtypes: int64(3), object(5)

I can't see why this is happening. Am I doing something wrong here? Any pointer is welcome! Thanks.

Answer 1

df.head(n) returns a DataFrame holding the first n rows of df. Now to display a DataFrame pandas checks by default the width of the terminal, if this is too small to display the DataFrame a summary view will be shown. Which is what you get in the second case.

Could you increase the size of your terminal, or disable autodetect on the columns by pd.set_printoptions(max_columns=10) ?

Answer 2

Try the below code segment:

from IPython.display import display
display(df.head())

Answer 3

 DataFrame.head(n=5)

Return the first n rows.

This function returns the first n rows for the object based on position. It is useful for quickly testing if your object has the right type of data in it.

Parameters:

n : int, default 5

Number of rows to select.

Returns:

obj_head : type of caller

The first n rows of the caller object.